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Job-Descriptions-JobAnalyze_6k

id,role,type,job_desc,year,qualification,experience,tech_skills,soft_skills
4,AI Engineer,Senior,"6+ years full-stack software engineering experience building scalable web applications, services, and APIs
Proficiency in JavaScript/TypeScript and/or Python, and comfort working across the stack including frontend development (React or similar frameworks)
Experience building backend systems, working with various datastores such as (Postgres/pgvector, Pinecone, Redis) and designing APIs.
Demonstrated curiosity and hands-on experience with AI tools and applications - using modern AI models, agentic IDEs, or building AI-enabled workflows or prototypes.
Experience building or experimenting with custom developed agentic systems, workflow orchestration tools (n8n), or Agentic browser automation
A high degree of ownership and initiative, with the ability to operate independently in ambiguous problem spaces
Excellent communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences
Experience collaborating cross-functionally and building trust with stakeholders at all levels of the organization
Direct experience integrating automated AI Evaluation/Testing/Observability suites to continuously test model effectiveness leveraging platforms such as DeepEval, Langfuse/LangSmith or similar 
",2026,Not Specified,5-10,"Python, Javascript, React, Full Stack, SQL, APIs, ML, TesnorFlow/PyTorch, n8n","Communication, Problem Solving"
7,AI Engineer,Senior,"5-10 years overall experience
3+ years of hands-on Power BI enterprise delivery
2+ years of SAP BusinessObjects migration experience (or equivalent BI migration)
SAP BusinessObjects: Universes (UNV/UNX), WebI, contexts, prompts, joins, aggregate awareness
Power BI / Fabric: Data modeling, DAX, calculation groups, Tabular Editor, Power BI Service governance
AI & Automation: Azure OpenAI / LLMs, prompt engineering, metadata and document parsing
Strong SQL and data engineering fundamentals.",2026,Not Specified,5-10,"Python, SQL, PowerBI, SAP, LLMs, Prompt Engineering, Data Engineering","Communication, Problem Solving"
11,AI Engineer,Senior,"4–6 years of experience in Data Science / Machine Learning / AI Engineering
Strong programming skills in Python
Hands-on experience with ML libraries such as Scikit-learn, Pandas, NumPy
Experience in building ML models (classification, regression, NLP, etc.)
Practical exposure to Generative AI / LLMs
Prompt engineering
RAG (Retrieval-Augmented Generation)
Chatbot or document-based AI solutions
Familiarity with frameworks like LangChain, LlamaIndex, or similar
Experience in building and consuming APIs
Strong problem-solving and analytical skills
Experience with cloud platforms (AWS / Azure / GCP)
Exposure to model deployment tools (Docker, MLflow, etc.)
Understanding of vector databases (FAISS, Pinecone, etc.)
Experience working in agile development environments",2026,Not Specified,5-10,"Python, Scikit-Learn, Pandas, NumPy, ML, LLMs, Prompt Engineering, RAG, LangChain, APIs, AWS/Azure, Docker, MLflow, VectorDB","Communication, Problem Solving"
12,AI Engineer,Senior,"Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or related fields.
2–5 years of hands-on experience in AI/ML or Generative AI development.
Experience building and deploying production-grade AI solutions.
Strong programming skills in Python.
Understanding of Artificial Intelligence and Machine Learning concepts.
Familiarity with APIs and software development fundamentals.
Strong analytical and problem-solving abilities.
Excellent communication and collaboration skills.
Experience with Generative AI platforms such as OpenAI, Gemini, Claude, or Hugging Face.
Knowledge of LangChain, LangGraph, CrewAI, AutoGen, or AI Agent frameworks.
Understanding of RAG architectures and Vector Databases (FAISS, ChromaDB, Pinecone, Weaviate, etc.).
Knowledge of SQL and database management.
Familiarity with cloud platforms such as AWS, Azure, or GCP.
Experience with Git, Docker, and CI/CD pipelines.
",2026,Bachelors/Masters,1-5,"Python, ML, APIs, GenAI, LangChain, LangGraph, CrewAI, AutoGen, RAG, VectorDB, SQL, Docker, Git, CI/CD, AWS/Azure","Communication, Problem Solving, Analytical Skills"
15,AI Engineer,Senior,"4–6 years of experience in Data Science / Machine Learning / AI Engineering
Strong programming skills in Python
Hands-on experience with ML libraries such as Scikit-learn, Pandas, NumPy
Experience in building ML models (classification, regression, NLP, etc.)
Practical exposure to Generative AI / LLMs
Prompt engineering
RAG (Retrieval-Augmented Generation)
Chatbot or document-based AI solutions
Familiarity with frameworks like LangChain, LlamaIndex, or similar
Experience in building and consuming APIs
Strong problem-solving and analytical skills
Experience with cloud platforms (AWS / Azure / GCP)
Exposure to model deployment tools (Docker, MLflow, etc.)
Understanding of vector databases (FAISS, Pinecone, etc.)
Experience working in agile development environments
",2026,Not Specified,5-10,"Python, ML, Pandas, NumPy, Scikit-Learn, GenAI, LLMs, Prompt Engineering, RAG,  LangChain, APIs, AWS/Azure, Docker, MLflow, VectorDB","Communication, Problem Solving"
20,AI Engineer,Senior,"Proven track record with at least 5 years of experience in a technical role focused on AI/ML.
Expertise in AI/ML frameworks, NLP, and Transformer technologies.
Strong experience with AWS cloud services, particularly for data processing and machine learning.
Proficiency in MLOps practices and familiarity with LLMOps.
Experience with FastAPI or similar frameworks for API development.
Knowledge of container orchestration with AWS EKS and Bedrock.
Team handling experience and architecture design experience.
Proficiency in creating and delivering Powerpoint presentations.
Knowledge of Responsible AI practices and Nvidia MLOps platform.
Experience with fine-tuning open-source AI/ML models.
Familiarity with DevOps practices, including continuous integration, deployment, and monitoring of AI models",2026,Not Specified,1-5,"Python, ML, NLP, MLOps, Feature Engineering, AWS/Azure, APIs","Communication, Problem Solving"
21,AI Engineer,Senior,"5+ years overall experience in software development, data science, or machine learning.
1+ year of hands-on experience developing AI applications with LLMs and systems such as retrieval-based methods, fine-tuning, or agent-based architectures.
Strong programming skills in Python and basics in SQL.
Expertise with LLM/SLM APIs, embeddings, and RAG systems.
Experience deploying on Google Cloud Platform (GCP) with Vertex AI, and IBM WatsonX.
Familiarity with agentic AI protocols and exposure to Agent Development Kits (ADKs).
Experience implementing Model Context Protocol (MCP) for agent coordination.
Prior exposure to LangGraph, AutoGen, or related orchestration frameworks.
1+ year of experience with frameworks like LangChain, LlamaIndex, OpenAI, or similar tools.
Good communication, stakeholder management and good aptitude, attitude to be flexible.
Experience in the functional side of Identity and Access management especially on identity governance, access management, privileged access, non-human identities, and worked on any IAM tools like SailPoint, Saviynt, CyberArk and SIEM/SOAR tools like Splunk etc.
Experience in strategy and roadmap work for Identity and Access management, especially in identifying use cases for automation, agentic AI workflows and roadmap for agentic AI lifecycle
2 or more years’ experience with developing Robotic Process Automation and/or automation efforts
2 or more years using Azure OR AWS cloud services
2 or more years skilled at data visualization (Tableau, PowerBI, etc.)
2 or more years with modern data engineering with APIs
2 or more years applying agile SDLC
Experience in enterprise-scale deployments of AI-driven platforms.
Contributions to open-source AI/ML projects are a plus.
",2026,Not Specified,5-10,"Python, APIs, LLMs, Prompt Engineering, LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen,  Anthropic /OpenAI SDKs, MCP, VectorDB, n8n, RAG, Agents, AWS/Azure, PowerBI","Communication, Problem Solving"
24,AI Developer,Senior,"Core Software Engineering (Required)
Strong hands-on development in Python / C# / TypeScript/JavaScript (or similar).
Experience building API-driven services and integrating distributed systems. 
Strong understanding of non-functional requirements: reliability, availability, scalability, performance, and cost.
Azure & Platform Engineering
Hands on experience with Azure AI Foundry for delivering enterprise GenAI solutions in an enterprise context.
Experience building serverless and asynchronous workloads using Azure Functions (including Durable Functions or equivalent).
Experience using queues and event driven messaging for decoupled, reliable workflows.
Experience working with ADLS for data ingestion, storage, and processing.
Experience using Azure Cognitive Services / Azure AI Services as part of AI solutions.
Azure Functions + Queues/Eventing (Required)
Experience with Azure Functions (including Durable Functions or equivalent orchestration patterns).
Experience implementing asynchronous patterns with queues/eventing for scale and reliability.
Vector Databases (Required)
Hands-on experience with vector databases / vector search, including enterprise deployment patterns
LLM-as-a-Judge Evaluation (Required)
Experience implementing evaluation approaches that include LLM-as-a-Judge (or equivalent automated evaluation patterns) for quality monitoring and continuous improvement.
Agent 365 (A365) + Governance Alignment (Required)
Familiarity/experience working in environments using Agent 365 (A365)-style lifecycle management concepts (e.g., agent registry, governance, monitoring/observability, and access controls)
Runtime Security / Runtime Protection (Required)
Experience delivering solutions with runtime protection expectations (runtime security controls, access controls, and monitoring alignment as defined by enterprise governance).
Experience integrating AI services into enterprise automation platforms (e.g., Power Platform, ServiceNow).
Familiarity with Azure AI services and data platforms.
",2026,Not Specified,5-10,"Python, Javascript, AWS/Azure, VectorDB, LLMs, Agent 365","Communication, Problem Solving"
25,AI Engineer,Senior,"15+ years of overall IT experience
Strong experience in AI Architecture
Hands-on experience in Agentic AI
Strong experience in AI Automation
Strong programming skills in Python
Good experience in REST APIs
Strong knowledge of Azure DevOps
Hands-on experience in CI/CD
Experience with GitHub
Strong solution design and stakeholder management skills
Experience in enterprise AI transformation initiatives
Exposure to cloud-based AI services
Experience in API integration architecture
Understanding of secure AI solution deployment
Experience mentoring teams and driving architecture governance
",2026,Not Specified,15+,"Python, ML, APIs, AWS/Azure, CI/CD, Github, Git, ","Communication, Problem Solving"
31,AI Developer,Senior,"trong hands-on experience in Python backend development.- Proven expertise with Agentic AI frameworks such as :i. LangGraphii. CrewAIiii. AutoGeniv. LangChain- Experience working with Model Context Protocol (MCP) tools and integrations.- Strong proficiency in FastAPI and modern API development.- Experience with cloud platforms :i. AWS (Bedrock preferred)ii. Microsoft Azure (AI Foundry preferred)- Hands-on experience with :i. Dockerii. Kubernetesiii. CI/CD pipelinesiv. Cloud security and governancePreferred Skills :- Experience with Retrieval-Augmented Generation (RAG) architectures.- Knowledge of vector databases and semantic search solutions.- Familiarity with observability, monitoring, and AI model evaluation frameworks.- Understanding of enterprise AI governance, security, and compliance requirements.Education :- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.- Any Graduate with relevant experience is welcome to apply. ",2026,Bachelors,5-10,"Python, LangChain, LangGraph, CrewAI, AutoGen, MCP, APIs, AWS/Azure, Docker, Kubernetes, CI/CD, RAG, VectorDB","Communication, Problem Solving"
32,AI Developer,Senior,"To qualify for the role you must have B.E/ B.Tech/ MCA/ MS /M.Tech or equivalent degree in Computer Science discipline. Minimum 4 – 8 years of experience in IT industry with at least 2+ years of experience in AI. Proven track record of working in AI projects from inception to successful deployment. Strong programming skills, preferably in Python, and experience with machine learning frameworks. Exposure / Experience in cloud services like Azure for deploying machine learning models and leveraging cloud-based machine learning services. Familiarity with relational databases like SQL Server / My SQL / PostgreSQL. Familiarity with Docker, Kubernetes, or similar tools for containerization and orchestration of machine learning applications. Knowledge / Experience in AI frameworks and technologies, such as GANs, transformers, and reinforcement learning. Hands-on experience in developing Generative AI solutions using Large Language models preferably Azure OpenAI. Excellent problem-solving skills and the ability to work in a fast-paced, dynamic environment. Strong communication skills to effectively collaborate with team members and stakeholders. ",2026,Masters,5-10,"Python,  ML, AWS/Azure, SQL, Docker, Kubernetes, LLMs","Communication, Problem Solving"
33,AI Developer,Senior,"• 3–6 years of software development experience, with solid hands-on experience in AI/ML or LLM application development.
• Strong proficiency in Python.
• Practical experience building APIs and backend services using FastAPI or a similar backend framework.
• Experience working with PostgreSQLor similar SQL/relational databases.
• Hands-on experience integrating LLMs into real applications.
• Goodunderstanding of prompt engineering, structured outputs, and retrieval-based workflows.
• Understanding of core AI/MLand data science concepts, including training data, model evaluation, embeddings, classification, and basic fine-tuning concepts.
• Exposure to model training or training support workflows, including data preparation and evaluation.
• Familiarity with backend integration patterns involving APIs, databases, async processing, and service-to-service communication.
• Ability to debug issues across prompts, model behavior, application logic, and data flow.
• Strong problem-solving skills and ability to work independently on implementation tasks.
• Experience with production use of OpenAI or comparable LLM platforms.
• Familiarity with embeddings, vector search, semantic retrieval, and RAG workflows.
• Experience with agent-style workflows, orchestration patterns, multi-step pipelines, or tool-calling systems.
• Awareness of recentAI ecosystem developments such as MCP, tools/skills patterns, and evolving agent integration approaches.
• Experience with batch jobs, background workers, schedulers, or queue-based processing.
• Familiarity with Docker and containerized deployments.
• Exposure to AWSor similar cloud platforms.
• Understanding ofAI observability, token usage, and cost-aware implementation.
• Experience contributing to technical design and solution planning ",2026,Not Specified,5-10,"Python, APIs, SQL, LLMs, Prompt Engineering, RAG,  MCP, VectorDB, Docker,  AWS/Azure","Communication, Problem Solving"
34,AI Engineer,Senior,"- Experience in publishing research or contributing to open source AI initiatives
- Designing AI systems for regulated or enterprise environments
- Understanding of AI governance, responsible AI practices, and compliance frameworks
- Experience mentoring technical teams or leading research initiatives

In addition to your technical skills and qualifications, you are expected to demonstrate baseline proficiency in enterprise-approved AI tools as part of your day-to-day responsibilities. This includes consistent use of AI tools such as GitHub Copilot, Microsoft 365 Copilot, and other GenAI platforms approved by the enterprise, leveraging AI tools to enhance coding, documentation, data analysis, and decision-making workflows, and staying current with evolving AI capabilities and features to improve delivery quality and velocity. 
",2026,Masters,5-10,"Python, GenAI, LLMs","Communication, Problem Solving"
42,AI Engineer,Senior,"Python · JS/TS · Neo4j/Cypher · MongoDB · PostgreSQL · FastAPI · LLM APIs · Vector databases · LoRA/PEFT · Docker · Linux CLI
What we value Side projects nobody asked you to build. Open-source contributions. Intellectual curiosity and ownership over any specific framework pedigree. 
AWS or GCP working knowledge
Annotation pipeline or ML dataset preparation experience",2026,Not Specified,1-5,"Python, Javascript, SQL, LLMs, APIs, VectorDB, ML, AWS/Azure","Communication, Problem Solving"
44,AI Engineer,Senior,"You will focus on creating reusable agent architectures, integrating enterprise APIs, and implementing observability for production AI systems. This is a leadership-focused role that requires deep expertise in Python and modern LLM orchestration techniques. Must have: 5+ years of experience; Deep experience with LangGraph, CrewAI, or AutoGen; Advanced prompt engineering and function calling; Expert-level Python; Experience designing stateful, scalable AI systems; Ability to lead AI initiatives from zero to production. Required tools: langgraph, crewai, autogen, python, llm, prompt engineering, mops. ",2026,Not Specified,5-10,"Python, ML, APIs, LLMs, LangChain, LangGraph, CrewAI, AutoGen, Prompt Engineering, MLOps","Communication, Problem Solving"
45,AI Engineer,Senior," Strong experience in Artificial Intelligence, Machine Learning (ML), and Generative AI (GenAI)
• Hands-on with LLMs, RAG pipelines, NLP
• Experience with LangGraph / AI workflow orchestration
• Proficiency in Python, FastAPI, API development
• Strong knowledge of SQL and NoSQL databases
• Experience in system design and scalable architecture
• Experience with vector databases (Pinecone, FAISS, Weaviate)
• Knowledge of cloud platforms (AWS, Azure, GCP)
• Exposure to MLOps and AI deployment pipelines
Bachelor’s degree in Computer Science, Engineering, or related field (Any Graduate with relevant experience is welcome)",2026,Bachelors,5-10,"Python, ML, GenAI, LLMs, RAG, NLP, LangChain, LangGraph, APIs, SQL, System Design, VectorDB, MLOps, CI/CD, AWS/Azure","Communication, Problem Solving"
52,AI Engineer,Senior,"Pytho n as the primary language for data science and ML development (Pandas, NumPy, Scikit-learn
Familiarity with
SQ L for data querying and manipulation across modern data warehouses (e.g., BigQuery, Snowflake, PostgreSQL
(Nice to have) Working knowledge of deep learning frameworks such as
PyTorc h or
TensorFlo w for model experimentatio n
LLM & Generative AI Tooling
Hands-on experience working with
large language model API s, including providers such as OpenAI, Anthropic, or Google
Strong command of
prompt engineering technique s, including few-shot prompting, chain-of-thought reasoning, and structured output design
Experience with
open-source LLM s (e.g., Mistral, LLaMA) and an understanding of when to apply open vs. proprietary models
Agentic Orchestration & RAG
Practical experience building
RAG (Retrieval-Augmented Generation) pipeline s, including chunking strategies, embedding models, and retrieval tuning
Familiarity with
agentic orchestration framework s such as LangChain, LangGraph, LlamaIndex, CrewAI, or AutoGe
Experience integrating
vector database s (e.g., pgvector, Pinecone, Weaviate, ChromaDB) into search and retrieval workflow
Understanding of
tool/function callin g patterns for LLM-driven automation
Evaluation & Experimentatio
Ability to define and implement
""good enough"" metric s and evaluation frameworks for POC validation
Experience with
LLM evaluation librarie s such as RAGAS, TruLens, or DeepEva
Familiarity with
experiment tracking tool s such as MLflow or Weights & Biases
Comfort with
cost and latency profilin g of LLM-based systems to inform feasibility decisions
Data & Infrastructure
Comfortable working within
cloud environment s (AWS, GCP, or Azure) for data access, compute, and API integration
Ability to integrate with
REST API s and third-party data sources during prototyping
Proficiency with standard development tools:
Gi t, Jupyter notebooks, VS Code ",2026,Bachelors,5-10,"Python, SQL, TensorFlow/PyTorch, ML, Pandas, NumPy, Scikit-Learn, LLMs, GenAI, APIs, OpenAI, RAG, LangChain, LangGraph, CrewAI, or AutoGen, VectorDB, Prompt Engineering, MLflow, Git, Github, AWS/Azure","Communication, Problem Solving, Analytical Skills"
53,AI Engineer,Senior,"Must Have Skills/Project Experience/Certifications:
• 3 - 6 years of hands-on experience of consulting/ industry experience
• Python: 4+ years with FastAPI, asyncio, data processing libraries
• AI/ML: Experience with LLMs, prompt engineering, fine-tuning, RAG systems
• CrewAI: Knowledge of multi-agent frameworks, agent orchestration patterns
• APIs: Integration with Anthropic, OpenAI, Google AI services
• Database: Vector databases, PostgreSQL, data modeling for AI workloads
• Cloud: Experience with cloud-based AI services and deployment
Good to Have Skills/Project Experience/Certifications:
• Experience with Langchain, LlamaIndex, or similar frameworks is highly encouraged
Education:
• BE/B.Tech/M.C.A./M.Sc (CS) degree or equivalent from accredited university ",2026,Bachelors/Masters,1-5,"Python, APIs, LLMs, Prompt Engineering, RAG, ML, CrewAI, VectorDB, SQL, LangChain, LangGraph","Communication, Problem Solving"
54,AI Engineer,Senior,"AI Agent Engineering
LangGraph or equivalent graph-based agent frameworks.
Multi-step reasoning pipelines.
Tool usage and orchestration.
State management and conversational workflows.
RAG & Vector Search
End-to-end RAG pipeline design and implementation.
Experience with vector databases such as:
Pinecone
Qdrant
pgvector
Weaviate
Chunking strategies and retrieval optimization.
Retrieval evaluation methodologies.
LLM Integration
OpenAI, Gemini, and Anthropic SDKs.
Prompt engineering and prompt optimization.
Structured JSON outputs.
Context window management.
Multi-provider LLM integrations.
Python Backend Development
Python 3.12
FastAPI
Async Python
Pydantic
SQLite
PostgreSQL
Redis
Pytest
Full-Stack Development
React
Next.js
TypeScript
Modern frontend architecture
API integration and state management
ML Engineering Fundamentals
Evaluation pipelines
Golden datasets and test suites
Regression tracking
Model performance monitoring
Good to Have
GIS & Mapping
ArcGIS REST APIs
GeoJSON
MapLibre GL JS
Spatial queries
(Strong advantage for initial project assignments.)
Data Visualization
Recharts
D3.js
Equivalent charting libraries
Cloud & DevOps
Docker
Azure
AWS
CI/CD pipelines
OIDC Authentication
Product Thinking
Ability to understand and interpret Figma designs.
Evaluate trade-offs between engineering effort and business value.
Deliver solutions aligned with business objectives.
Technologies You'll Work With
LayerTechnology Stack
Agent Frameworks
LangGraph, LangChain
LLM Providers
Gemini, OpenAI, Anthropic
Backend
Python 3.12, FastAPI, SQLite, Redis
Frontend
Next.js 15, React 19, TypeScript, Zustand
Data & Visualization
Recharts, GeoJSON, MapLibre GL JS
Infrastructure
Docker, Azure Pipelines, Azure AD ",2026,Not Specified,1-5,"Python, ML, LangChain, LangGraph, RAG, VectorDB, LLMs, APIs, Prompt Engineering, SQL, React, Javascript, Docker, CI/CD, AWS/Azure","Communication, Problem Solving"
56,AI Engineer,Senior,"Lead the full lifecycle of Generative AI solutions from design and development to deployment encompassing LLM-powered workflows, RAG pipelines, OCR, and Agentic AI systems.
Architect and implement secure, scalable AI infrastructures using GCP, AWS, or Azure.
Apply LLMOps best practices, including fine-tuning, advanced prompt engineering, and model optimization, to maximize performance and contextual accuracy.
Design and maintain APIs and microservices (FastAPI, REST, Spring Boot) to integrate AI capabilities into enterprise systems.
Build and optimize data pipelines and manage vector databases and Elasticsearch for efficient knowledge retrieval and decision-making.
Implement MLOps, CI/CD, and DevOps pipelines using Kubernetes, Docker, Jenkins, and Ansible for automated deployment and monitoring.
Ensure system reliability and observability through logging, monitoring, and infrastructure-as-code practices (e.g., ELK stack).
Collaborate cross-functionally with product, engineering, and business teams to align AI solutions with organizational goals.
Mentor and guide junior engineers, setting best practices for scalable, maintainable AI development.
Required Experience:
2+ years of professional software engineering experience focused on Generative AI / LLMbased applications. 
",2026,Not Specified,1-5,"Python, LLMs, MLOps, APIs, AWS/Azure, VectorDB, CI/CD, Docker, Kubernetes, GenAI","Communication, Problem Solving"
60,AI Engineer,Senior,"Experience in AI/GenAI solution for prompt engineering, architecture, consulting, and enterprise architecture
Experience in software development
Excellent communication skills (customer facing position)
A deep understanding of GenAI/ML technologies and their implementations
Experience in the financial, healthcare, or insurance industries is a plus
Bachelor's/Master's degree in Computer Science/data science or related field
Demonstrated expertise in statistical analysis and machine learning concepts, with proficiency in Python
Solid understanding and experience in designing, implementing, and optimizing end-to-end machine learning pipelines.
Minimum 2+ years of experience in Generative AI and Minimum 2+ years in traditional Machine Learning, with a focus on the creation, training, and deployment of services such as recommendation engines, deep learning, and generative AI models.
1. LLM (GPT); prompt engineering for reflex, model and self-learning agents
2. Facility with Python to code wrappers, interface with APIs, develop utilities
3. Experience with packages such as LangChain and LangGraph
4. Experience with assembling intelligent AI agents to implement variety of use cases
5. A recent use case for Agentic AI powered by LLMs: NLQ to SQL translator
6. You MUST have the ability to think through clearly for a solution design,
Experienced in Large Language Models, Transformers, CNN, TensorFlow, Scikit-learn, Pytorch, NLP libraries, Embedding Models, Vector Databases
Hands-on experience with OpenAI, Llama/Llama2 and other open-source models, and Azure OpenAI models Education- Engineering, Math and Statistics foundation, (Data Science/Computer Science preferred)",2026,Bachelors/Masters,1-5,"Python, ML, GenAI, APIs, LLMs, Prompt Engineering, LangChain, LangGraph, SQL, TensorFlow/Pytorch, Scikit-Learn, NLP, OpenAI, VectorDB","Communication, Problem Solving"
61,AI Engineer,Senior,"Artificial Intelligence & Machine Learning
• Machine Learning
• Deep Learning
• Generative AI
• Reinforcement Learning
• Neural Networks
• Predictive Analytics
Large Language Models (LLMs)
• OpenAI GPT Models
• Claude AI
• Google Gemini
• Llama Models
• Mistral AI
• LangChain
• LangGraph
• CrewAI
• AutoGen
Programming Languages
• Python (Expert)
• JavaScript / TypeScript
• C#
• Java
• SQL
AI Frameworks & Libraries
• TensorFlow
• PyTorch
• Scikit-Learn
• Hugging Face Transformers
• OpenCV
• Keras
Backend Development
• FastAPI
• Django
• Flask
• Node.js
• REST APIs
• GraphQL
Frontend Development
• React.js
• Next.js
• Angular
• Vue.js
Mobile Development
• Flutter
• React Native
• Native Android
• Native iOS
Desktop Development
• Electron.js
• .NET Desktop Applications
• Python Desktop Applications
• Cross-platform Desktop Solutions
Cloud & DevOps
• AWS
• Azure
• Google Cloud Platform
• Docker
• Kubernetes
• CI/CD Pipelines
Databases
• PostgreSQL
• MySQL
• MongoDB
• Redis
• Vector Databases (Pinecone, Weaviate, ChromaDB)
Preferred Qualifications
• Bachelor's or Master's Degree in Computer Science, Artificial Intelligence, Data Science, or related field.
• Experience building AI products at scale.
• Strong portfolio of deployed AI solutions.
• Experience with enterprise SaaS platforms.
• Knowledge of AI governance and responsible AI practices.
• Experience managing technical teams and AI projects ",2026,Bachelors/Masters,5-10,"Python, ML, GenAI, OpenAI, LangChain, LangGraph, CrewAI, AutoGen, Javascript, Java, C#, SQL, TensorFlow/PyTorch, Scikit-Learn, Hugging Face, APIs, Django, React, Docker, Kubernetes, CI/CD, AWS/Azure, VectorDB","Communication, Problem Solving, Analytical Skills"
64,AI Developer,Senior,"• Strong experience in enterprise backend application development.
• Good experience designing and building microservices-based applications.
• Hands-on experience with Java / Spring Boot, Python / FastAPI, Node.js, .NET, or
similar backend frameworks.
• Strong understanding of REST APIs, service contracts, JSON, authentication,
authorization, and integration patterns.
• Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or
Oracle.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with Docker and container-based application deployment.
• Understanding of event-driven architecture using SQS, Kafka, RabbitMQ,
EventBridge, Step Functions, or similar tools.
• Good understanding of logging, monitoring, error handling, retry logic, performance
tuning, and production support.
• Strong problem-solving ability and comfort working on complex enterprise
workflows.
AI / LLM Skills Preferred
• Exposure to LLM-based application development using OpenAI, Azure OpenAI, AWS
Bedrock, Anthropic, Llama, or similar platforms.
• Understanding of prompt engineering, structured outputs, confidence scoring, and
response validation.
• Experience with RAG, embeddings, vector search, semantic search, or knowledge
retrieval.
• Familiarity with LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI,
AutoGen, or similar frameworks is useful but not mandatory.
• Ability to work with AI engineers / data scientists to integrate models, prompts,
retrieval pipelines, and recommendation logic into enterprise applications. ",2026,Not Specified,5-10,"Python, .NET, APIs, Java, SQL, AWS/Azure, ML, LLMs, OpenAI, Prompt Engineering, RAG, VectorDB,  LangChain, LangGraph, CrewAI, AutoGen","Communication, Problem Solving, Analytical Skills"
66,AI Engineer,Senior,"• Building production AI/LLM applications (not just prototypes)
• Working with LLMs, APIs, and tool integrations
• Designing multi-step workflows or pipelines
• Writing clean, scalable backend systems (Python/Go/Node)
• Debugging and improving system reliability and performance
• Understanding of how systems fail and how to handle edge cases
• Agent frameworks (LangGraph, LangChain, AutoGen, CrewAI, etc.)
• Workflow orchestration concepts (RAGs, pipelines, schedulers)
• Experience with event-driven systems (Kafka, queues, async processing)
• Basic understanding of:
• retries / idempotency
• observability / logging
• distributed systems",2026,Bachelors,5-10,"Python, LLMs, ML, LangGraph, LangChain, AutoGen, CrewAI, RAG, ","Communication, Problem Solving"
67,AI Engineer,Senior,"• 2+ years hands-on AI/ML experience
• Strong Python + PyTorch
• Experience fine-tuning LLMs (PEFT / LoRA / quantization)
• Experience with RAG + vector databases
• Hands-on with diffusion pipelines (Stable Diffusion preferred)
• Production mindset monitoring, versioning, cost optimization
• Comfortable in a fast-paced startup environment
• Experience with AI companion or conversational AI products
• Experience with ComfyUI workflows
• GPU infra optimization experience
• Real-time streaming generation systems ",2026,Bachelors,1-5,"Python, Tensorflow/Pytorch, LLMs, RAG, VectorDB","Communication, Problem Solving"
69,AI Developer,Senior,"6+ years of hands-on experience in AI/ML solution architecture and delivery
Proven experience implementing AI/ML use cases for customer-facing platforms
Strong background in analytics, predictive modeling, and operational intelligence initiatives
Experience designing scalable AI solutions that drive business outcomes and enhance customer engagement
Expertise in Machine Learning, Deep Learning, and enterprise AI architectures
Strong stakeholder management and technical leadership capabilities",2026,Not Specified,15+,"Python, ML, LLMs","Communication, Problem Solving"
70,AI Engineer,Senior,"• 3+ years of overall IT experience with significant exposure to AI/ML architecture.
• Strong expertise in Python programming.
• Hands-on experience with Generative AI (GenAI) technologies and Large Language Models (LLMs).
• Experience designing and implementing Agentic AI solutions.
• Strong knowledge of the Databricks Platform .
• Proficiency in SQL and handling complex data structures.
• Good understanding of JSON structures , APIs, and system integrations.
• Proven experience in technical architecture , solution design, and enterprise application integration.
• Strong problem-solving, communication, and stakeholder management skills. ",2026,Not Specified,1-5,"Python, ML, GenAI, LLMs, Agents, SQL, APIs, ","Communication, Problem Solving"
72,AI Engineer,Senior,"• Prior 5–9 years of experience in data science, ML engineering, or AI development, with 2+ years focused on Generative AI.
• Strong hands-on experience with LLMs, transformers, embeddings, and vector databases.
• Proficiency in Python and GenAI frameworks (LangChain, LlamaIndex, Haystack, Hugging Face).
• Experience with fine-tuning techniques (LoRA, PEFT, instruction tuning).
• Experience designing multi‑agent systems, including orchestration, coordination, and distributed reasoning.
• Familiarity with MLOps tools, CI/CD pipelines, and model monitoring.
• Familiarity with 3D deep learning and large scale point cloud processing is a plus.
• Experience working in fast paced startup environment (preferred).
• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field. ",2026,Bachelors/Masters,5-10,"Python, GenAI, LangChain, LangGraph, MLOps, CI/CD","Communication, Problem Solving"
73,AI Engineer,Senior,"pytestSeleniumPostman
Languages
Python
Testing focus
API TestingUI Testing
Also listed
Ai testingLlm testingRag evaluationPrompt engineeringDeepevalPromptfooLangsmithRagasData quality testingGreat expectationsDbtMachine learning lifecycleAutomation testingCi/cd ",2026,Not Specified,5-10,"Python, Pytest, APIs, LLMs, RAG, Prompt Engineering, ML, LangChain, LangGraph, CI/CD","Communication, Problem Solving"
74,AI Developer,Senior,"• Bachelor’s degree in computer science, Engineering, Data Science, or related technical field
• Master's degree preferred (Computer Science, AI/ML, or MBA with technical focus)
• 6+ years of software development experience with 2+ years focused on AI agent development
• 2+ years of hands-on experience with Azure AI Foundry or similar agent development platforms
• Proven experience building and deploying production AI agents and automated workflows
• Microsoft Azure AI Foundry: Deep expertise in Azure AI services ecosystem
• Agent Development: Multi-agent systems (MOE), reasoning frameworks, and orchestration
• Workflow Design: Prompt flow, automation pipelines, and human-in-the-loop systems
• Post-Training Techniques: Fine-tuning, instruction tuning, RLHF, and domain adaptation
• Model Evaluation: Performance metrics, benchmark development, and A/B testing frameworks
• Consulting mindset with a strong bias for action.
• Adept at connecting strategy to execution and simplifying complexity.
• Passion for enabling people and driving business transformation through AI. ",2026,Bachelors/Masters,5-10,"Python, AWS/Azure, Agents, LLMs, ML","Communication, Problem Solving"
78,AI Engineer,Senior,"• e4–10 years of software engineering with substantial experience building distributed systems, infra, or ML platforms
• .Deep practical experience integrating and deploying LLMs in production (RAG, retrieval, embeddings pipelines)
• .Hands-on experience with agent orchestration frameworks (LangGraph / LangChain or custom agent runtimes) and stateful workflow design
• .Proven track record building observability, cost controls, and policy enforcement for production services
.Preferred / differentiator
• sExperience building or contributing to open-source LLM orchestration tools (LangGraph, LangChain, or similar)
• .Familiarity with enterprise constraints: on-prem/cloud hybrid deployments, data residency, compliance requirements
• .Background in security, privacy, or model governance for LLMs
• .Demonstrated leadership in cross-functional projects and direct customer engagement ",2026,Not Specified,5-10,"Python, ML, LLMs, RAG, LangChain, LangGraph ","Communication, Problem Solving"
79,AI Engineer,Senior,"Qualifications Bachelor’s/Master’s Degree or equivalent. 8+ years in software/ML engineering, 1.5+ years hands-on with LLMs/GenAI and agentic frameworks. Proven track record shipping production AI systems on at least one hyperscaler (Azure/AWS/GCP). Experience leading 3–6 engineers and owning end-to-end delivery. Required Skills Strong Python experience to build multiple AI-ML/ GenAI Solutions. Should have experience working on Agent orchestration with leading frameworks like LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen . Strong experience working on Vector DB like Pinecone, Milvus, Redis/pgvector); Should have experience working on hybrid search and re-rankers Should have experience on evaluation & observability Experience working on SQL Query , NLP, CV, Deep Learning Algorithms Should have working experience with Open Source Models Experience on UI/UX will be added advantage. #GenAINTT RESUME SELECTION Guidelines: Delivered at least 2 GenAI/Agentic AI solutions for clients Extensive experience of minimum 6+ years on Python Led 2–3 successful client  ",2026,Bachelors/Masters,5-10,"Python, ML, LLMs, GenAI, AWS/Azure, LangChain, LangGraph, CrewAI, AutoGen, VectorDB, RAG, SQL, NLP","Communication, Problem Solving, Analytical Skills"
80,AI Engineer,Senior,"• Building and deploying autonomous agents
• LangChain framework for developing applications
• Retrieval Augmented Generation (RAG) systems
• Large Language Models (LLMs) and their APIs
• Solid understanding of safety principles and best practices
• Resolving hallucinations in the outcomes
Mandatory Skill sets:
• Advanced Python programming with expertise in async programming and API developmenT
• Experience with vector databases and embedding models
• Proficiency in implementing RAG pipelines and knowledge retrieval systems
• Familiarity with prompt engineering and LLM optimization techniques
• Experience with development frameworks and tools
• Knowledge of modern software development practices (Git, CI/CD, testing)
Preferred Skill sets:
• Multiple LLM providers (OpenAI, Anthropic, etc.)
• Tools for agent orchestration and workflow management
• Natural Language Processing (NLP) techniques
• Container technologies (Docker, Kubernetes)
• Understanding of semantic search and information retrieval concepts
• Knowledge of agent alignment and safety considerations
Years of experience required :
1+yrs to 3+yrs
Education qualification -Full Time :
BE/Btech/MCA/Mtech/MBA ",2026,Bachelors/Masters,1-5,"Python, LLMs, ML, LangGraph, LangChain, RAG, APIs, OpenAI, NLP, VectorDB, Git, Github, CI/CD, Docker, Kubernetes","Communication, Problem Solving"
81,AI Engineer,Senior,"Software Requirements
• In-depth expertise in Generative AI and Agentic AI technologies
• Programming proficiency in Python, with experience in frameworks such as PyTorch, TensorFlow, or similar for AI model development
• Familiarity with cloud AI services like AWS SageMaker, Azure Machine Learning, or GCP AI platform
• Understanding of APIs and integrations for deploying AI models effectively
• Experience with data management tools and version control systems like Git
• Knowledge of blockchain and IoT as they relate to AI deployment
• Experience using automation and orchestration tools in AI workflows 
• Programming Languages: Python (required), R, Java (preferred)
• AI Frameworks & Libraries: PyTorch, TensorFlow, GPT/Transformers, OpenAI API, Hugging Face (required)
• Data Management: Data preprocessing, management, and model training data pipelines
• Cloud Technologies: AWS, Azure, GCP (preferred)
• Model Deployment & APIs: REST API development, containerization with Docker, orchestration with Kubernetes
• Tools & Methodologies: Agile, CI/CD pipelines, Git version control, model versioning tools
• Security & Ethics: Data privacy, AI fairness, and compliance considerations
Experience Requirements
• At least 5-7 years of experience in software development and leading technology projects
• Proven track record of delivering AI solutions that enhance business operations
• Experience mentoring engineering teams in AI project execution
• Industry experience in banking, finance, or enterprise environments preferred
• Alternative experience: extensive innovation in AI, natural language processing, or digital transformation initiatives ",2026,Bachelors/Masters,5-10,"Python, GenAI, TensorFlow/Pytorch, AWS/Azure, MCP, ML, APIs, Git, Github, Python, Java, Docker, Kubernetes, CI/CD, NLP","Communication, Problem Solving, Analytical Skills"
82,AI Engineer,Senior,"• Strong academic record — B.Tech / B.E. / M.Tech / MCA in Computer Science or a related field from a reputable institution (or equivalent).
• 2–3 years in software / integration engineering, with hands-on third-party API and systems-integration work.
• Strong data structures, algorithms, and problem-solving skills.
• Hands-on MCP experience (building or integrating MCP servers/clients) is a strong plus; otherwise solid API-integration depth with eagerness to ramp on MCP.
Preferred Certifications
• OAuth 2.0 / OpenID Connect or relevant identity/security certification
• Any recognised cloud certification (Azure / AWS / GCP) is a plus
Soft Skills & Cultural Fit
• Security-first instinct — assumes external services are hostile until proven otherwise.
• Strong analytical and debugging skills across system boundaries (auth, networking, schema mismatches).
• Clear written communication — produces precise integration docs and runbooks.
• Collaborative; comfortable engaging both internal engineers and external vendor teams. ",2026,Bachelors/Masters,1-5,"Python, MCP, APIs, AWS/Azure, ML","Communication, Problem Solving, Analytical Skills"
83,AI Engineer,Senior,"• Minimum of 4 years of experience as a software engineer
• Professional experience integrating LLMs into a software product (experience building a chatbot or using simple coding assistants is not sufficient)
• Experience shipping a production system where a self-improving agent drove the iteration on the system itself (e.g., designed its own tools, refined its own reward function, etc.)
• Experience curating evaluation or regression sets driving self-improving systems and defining measurable success criteria
• Experience with modern agent-orchestration tooling (e.g., LangChain, LangGraph)",2026,Not Specified,1-5,"Python, LLMs, LangChain, LangGraph, Agents, APIs, ","Communication, Problem Solving"
85,AI Engineer,Senior,"Senior AI/ML Engineer – GenAI, LLM, Data Science &

MLOps

Experience: 6–7 Years

Location: On-site

Employment Type: Full-time

Notice Period: Immediate Joiners, 15 Days to 1 Month Preferred

About the Role

We are looking for a highly skilled Senior AI/ML Engineer to lead the design, development,

deployment, and optimization of scalable AI solutions. 
",2026,Not Specified,5-10,"Python, ML, GenAI, LLMs, MLOps, APIs","Communication, Problem Solving"
86,AI Engineer,Senior,"- Significant experience in design (architecture, design patterns, reliability, and scaling) and implementation or enhancement of new and current systems
- Significant experience in system engineering involving analytical systems design and implementation
- Fluency and specialization with modern languages such as Java, C# or Python
- Experience in building products using microservices architectural patterns and extensible REST APIs
- Familiarity with continuous delivery and infrastructure as code
- Proven experience in cloud, DevOps, or AI modernization initiatives
- Strong understanding of LLMs, automation, and engineering toolchains
- Ability to translate AI innovation into business and productivity impact ",2026,Not Specified,1-5,"Python, System Design, Java, C#, AIPs, MLOps, LLMs","Communication, Problem Solving"
87,AI Engineer,Senior,"• Minimum four years of experience building, training, and deploying machine learning models with measurable real-world impact
• Deep proficiency in Python and frameworks such as PyTorch or JAX; expertise in model design and optimization
• Proven experience fine-tuning and deploying large pre-trained and foundation models including language and scientific models
• Strong understanding of model evaluation including benchmarking, cross-validation, and performance across data distributions
• Experience with distributed training and large-scale computing environments for high-performance model training
• Hands-on expertise optimizing models and pipelines for latency, throughput, cost, and production performance
• Experience with MLOps practices including experiment tracking, model versioning, reproducibility, and cloud deployment
• Strong problem-solving, collaboration, and communication skills with ability to drive engineering excellence in complex environments ",2026,Not Specified,5-10,"Python, ML, TensorFlow/Pytorch, LLMs, MLOps","Communication, Problem Solving"
88,AI Engineer,Senior,"Minimum four years of experience building, training, and deploying machine learning models with measurable real-world impact Deep proficiency in Python and frameworks such as PyTorch or JAX; expertise in model design and optimization Proven experience fine-tuning and deploying large pre-trained and foundation models including language and scientific models Strong understanding of model evaluation including benchmarking, cross-validation, and performance across data distributions Experience with distributed training and large-scale computing environments for high-performance model training Hands-on expertise optimizing models and pipelines for latency, throughput, cost, and production performance Experience with MLOps practices including experiment tracking, model versioning, reproducibility, and cloud deployment Strong problem-solving, collaboration, and communication skills with ability to drive engineering excellence in complex environments ",2026,Not Specified,5-10,"Python, ML, Git, Github, MLOps, TensorFlow/PyTorch","Communication, Problem Solving"
90,AI Engineer,Senior,"• • 6-12 years of software engineering experience, with at least 2 years focused on AI/ML application development.
• • Hands-on experience shipping LLM-powered applications to real users or stakeholders: RAG pipelines, prompt engineering at system level, agentic workflows.
• • Production-level proficiency in Python and/or TypeScript for rapid prototyping.
• • Experience with cloud AI platforms—AWS Bedrock strongly preferred; SageMaker, Azure AI, or Anthropic Claude acceptable.
• • Working experience with agentic AI frameworks: LangChain, LangGraph, CrewAI, AWS Strands Agents, Claude Managed Agents, AWS Agentcore, or equivalent.
• • Strong API integration skills: REST, webhooks, MCP or similar agent-to-service patterns.
• • Demonstrated ability to facilitate business discovery sessions and present demos to technical & non-technical stakeholders.
• • Experience pairing with distributed teams to develop production-grade agentic AI systems.
• • Primary interface with Lead AI Solutions Architects and business stakeholders.
• • Requires strong English communication, executive presence, and async documentation discipline.
• • Bachelor’s degree in computer science, Software Engineering, AI/ML, or related field.
• • Agile/Scrum experience.
• • Builds RAG pipelines, API integrations, agentic workflow components, and prompt systems.
• • Writes transition documentation, contributes to Confluence knowledge base.
• • Must demonstrate strong async communication, self-direction, and clean handoff discipline.
Required Experience
• • Has shipped at least one highly performant and reliable production grade LLM-powered agentic AI application to real users or business stakeholders (not just Kaggle or personal projects).
• • Can write production-quality Python or TypeScript.
• • Can explain what RAG is, what agentic workflows are, and when you would (and would not) use each.
• • Has worked with at least one cloud AI platform (AWS Bedrock preferred).
• • Comfortable with ambiguity — can define scope from an unstructured problem statement.
Preferred
• • Experience with AI evaluation frameworks, prompt testing, and LLM output quality assurance.
• • Background in digital marketing technology, SaaS platforms, or sales/marketing operations.
• • Familiarity with AI Development Lifecycle (AI-DLC) methodologies.
• • Experience with Agent-to-Agent(A2A) integration. ",2026,Not Specified,5-10,"Python, ML, RAG, VectorDB, APIs, LLMs, AWS/Azure, MCP, Agents, LangChain, LangGraph, Prompt Engineering","Communication, Problem Solving, Analytical Skills"
91,AI Engineer,Senior,"Responsibilities: Design and implement autonomous agents using LangChain / Crew.ai / SK / Autogen and other relevant frameworks Develop and optimize RAG systems for improved information retrieval and response generation Create robust evaluation frameworks for testing agent performance and safety Implement monitoring and logging systems for agent behavior Develop documentation and best practices for agent development Contribute to the improvement of agent architecture and capabilities Hands-on experience with: Building and deploying autonomous agents LangChain framework for developing applications Retrieval Augmented Generation (RAG) systems Large Language Models (LLMs) and their APIs Solid understanding of safety principles and best practices Resolving hallucinations in the outcomes Mandatory Skill sets: Advanced Python programming with expertise in async programming and API developmenT Experience with vector databases and embedding models Proficiency in implementing RAG pipelines and knowledge retrieval systems Familiarity with prompt engineering and LLM optimization techniques Experience with development frameworks and tools Knowledge of modern software development practices (Git, CI/CD, testing) Preferred Skill sets: Multiple LLM providers (OpenAI, Anthropic, etc.) Tools for agent orchestration and workflow management Natural Language Processing (NLP) techniques Container technologies (Docker, Kubernetes) Understanding of semantic search and information retrieval concepts Knowledge of agent alignment and safety considerations Years of experience required: 2 to 3+yrs Education qualification: Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or a related fields ",2026,Bachelors,1-5,"Python, ML, RAG, VectorDB, APIs, LLMs, AWS/Azure, MCP, Agents, LangChain, LangGraph, Prompt Engineering, Git, Github, CI/CD, AutoGen, CrewAI, GenAI, NLP, Docker, Kubernetes","Commuication, Problem Solving"
92,AI Engineer,Senior,"3+ years of overall IT experience with significant exposure to AI/ML architecture.
Solid expertise in Python programming.
Hands-on experience with Generative AI (GenAI) technologies and Large Language Models (LLMs).
Experience designing and implementing Agentic AI solutions.
Strong knowledge of the Databricks Platform.
Proficiency in SQL and handling complex data structures.
Good understanding of JSON structures, APIs, and system integrations.
Proven experience in technical architecture, solution design, and enterprise application integration.
Strong problem-solving, communication, and stakeholder management skills. ",2026,Not Specified,1-5,"Python, ML, GenAI, Agents, LangChain, LangGraph, LlamaIndex, SQL, APIs, System Design, LLMs","Communication, Problem Solving"
93,AI Engineer,Senior,"Key Skills:

• Python

• Machine Learning & Deep Learning

• TensorFlow / PyTorch

• NLP, Computer Vision, Generative AI

• AWS / Azure / GCP

• MLOps & Model Deployment

• APIs & Microservices

Responsibilities:

• Lead AI/ML projects from development to deployment.

• Build and optimize machine learning models and pipelines.

• Collaborate with business and technical teams to deliver AI solutions.

• Mentor and guide AI/ML engineers.

• Ensure best practices in model development and deployment.

• Stay updated with the latest AI and Generative AI technologies.

Requirements:

• 8–10 years of overall experience with strong expertise in AI/ML.

• Hands-on experience in Python and AI frameworks.

• Experience with cloud platforms and model deployment. 
",2026,Not Specified,5-10,"Python, ML, TensorFlow/PyTorch, NLP, GenAI, AWS/Azure, MLOps, APIs","Communication, Problem Solving"
95,AI Engineer,Senior,"• Experience with Large Language Models (LLMs) and Generative AI application development.
• Hands-on experience with LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks.
• Strong understanding of RAG, embeddings, vector search, and semantic retrieval techniques.
• Proficiency in Python and API integration.
• Experience integrating enterprise data sources and external tools into AI workflows.
• Familiarity with cloud-native platforms and data engineering environments.
• Ability to design scalable, modular, and production-ready AI architectures.
Preferred Skills
• Experience with vector databases such as Pinecone, Chroma, Weaviate, or pgvector.
• Exposure to MLOps, AI monitoring, and observability tools.
• Experience in enterprise software delivery or client-facing environments.
• Knowledge of modern web frameworks for AI-enabled applications.
Preferred Qualifications
• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Strong analytical, problem-solving, and communication skills.
• Ability to work independently and collaboratively in a fast-paced environment. ",2026,Bachelors,1-5,"Python, LLMs, GenAI, ML, LangChain, LangGraph, CrewAI, AutoGen, APIs, VectorDB, System Design, MLOps, ","Communication, Problem Solving, Analytical Skills"
96,AI Engineer,Senior,"You will be responsible for setting up scalable cloud environments, building seamless CI/CD pipelines, and establishing cutting-edge deployment frameworks for Large Language Models (LLMs) and foundational AI applications.Key Responsibilities1. GenAI & LLMOps InfrastructureDesign and manage cloud infrastructure tailored for hosting, fine-tuning, and serving Generative AI models.Implement and manage infrastructure for AI orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel).Optimize vector databases (e.g., Pinecone, Milvus, Qdrant, or pgvector in PostgreSQL) for highly efficient Retrieval-Augmented Generation (RAG) pipelines.Implement cost-optimization strategies for heavy compute resources (GPUs/TPUs).2. Core DevOps & Cloud EngineeringArchitect, scale, and maintain secure, cloud-native infrastructure utilizing AWS, Azure, or GCP.Orchestrate and manage containerized workloads using Docker and Kubernetes.Implement robust Infrastructure as Code (IaC) using Terraform, OpenTofu, or CloudFormation.Build, maintain, and optimize secure CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins) for automated software and model deployment.3. Monitoring, Observability & SecuritySet up advanced observability tools (Prometheus, Grafana, Datadog) to track both infrastructure health and AI model performance metrics (latency, token usage, drift).Collaborate with engineering teams to ensure highly secured IT solutions, embedding data privacy, vulnerability scanning, and guardrails for LLM prompts/outputs.Required Technical Skills & QualificationsExperience: 5+ years of total experience in DevOps/Cloud Engineering, with at least 1–2 years actively supporting AI/ML or GenAI workloads in production.AI/LLM Ecosystem: Practical exposure to deploying LLMs (OpenAI APIs, Hugging Face, Anthropic, or open-source models like Llama via Ollama/vLLM).Containerization & Orchestration: Deep expertise in Kubernetes (EKS, AKS, or GKE) and Docker.Infrastructure as Code: Proven mastery of Terraform.Databases: Familiarity with traditional databases (PostgreSQL, MongoDB) as well as vector stores.Programming: Strong scripting and automation skills in Python (highly preferred for AI workflows), Go (Golang), or Bash. ",2026,Not Specified,5-10,"Python, LLMs, CI/CD, MLOps, LangChain, LlamaIndex, RAG, VectorDB, SQL,  Docker, Kubernetes, AWS/Azure, Github, Git, OpenAI, APIs, Hugging Face","Communication, Problem Solving"
97,AI Engineer,Senior,"• 5+ years of experience in AI/ML engineering with strong software development fundamentals.
• Strong programming skills in Python; knowledge of SQL and Java is an advantage.
• Hands-on experience in Machine Learning, Deep Learning, and Natural Language Processing (NLP).
• Experience building Generative AI applications using Large Language Models (LLMs).
• Strong expertise in Prompt Engineering, Retrieval-Augmented Generation (RAG), AI Agents, and Agentic AI.
• Hands-on experience with AI frameworks such as LangChain, LangGraph, LlamaIndex, Hugging Face, and OpenAI SDK.
• Experience working with vector databases such as Pinecone, FAISS, ChromaDB, Milvus, or Weaviate.
• Proficiency in ML frameworks and libraries including PyTorch, TensorFlow, Scikit-learn, XGBoost, Pandas, and NumPy.
• Experience developing and deploying REST APIs using FastAPI or Flask.
• Good understanding of MLOps, including MLflow, Kubeflow, model deployment, monitoring, model versioning, and CI/CD pipelines.
• Experience with Docker, Kubernetes, Git, GitHub Actions, or Jenkins.
• Hands-on experience with at least one cloud platform: AWS, Azure, or GCP, including AI services such as SageMaker, Azure OpenAI, AWS Bedrock, or Vertex AI.
• Experience working with relational and NoSQL databases such as PostgreSQL, MySQL, MongoDB, or Redis.
• Knowledge of software engineering best practices, scalable system design, and Agile development methodologies.
• Excellent analytical, problem-solving, communication, and stakeholder management skills.
• Ability to work collaboratively in cross-functional teams and deliver production-grade AI solutions. ",2026,Not Specified,5-10,"Python, Java, SQL, NLP, GenAI, LLMs, RAG, Prompt Engineering, Agents, LangChain, LangGraph, LlamaIndex, Hugging Face, OpenAI, APIs, VectorDB, Pandas, Numpy, Scikit-Learn, TensorFlow/PyTorch, MLflow, MLOps, CI/CD, Git, Github, Docker, Kubernetes, AWS/Azure, System Design","Communication, Problem Solving"
98,AI Engineer,Senior,"• 8–10 years of software engineering experience.
• Strong hands-on experience with LangChain and LangGraph (Mandatory).
• Strong knowledge of Agentic AI and Large Language Models (LLMs).
• Proficiency in Python.
• Experience with RAG architectures, vector databases, embeddings, and prompt engineering.
• Experience integrating AI models through APIs and AI orchestration frameworks.
• Strong understanding of software design principles and scalable application architecture.
• Excellent analytical and problem-solving skills. ",2026,Not Specified,5-10,"Python, ML, LLMs, Agents, LangChain, LangGraph, RAG, VectorDB, System Design, Prompt Engineering","Communication, Problem Solving, Analytical Skills"
99,AI Engineer,Senior,"AI & Machine Learning
• Strong expertise in Machine Learning, Deep Learning, and Data Science.
• Hands-on experience with Generative AI and Large Language Models (LLMs).
• Experience with Prompt Engineering, Fine-Tuning, and Model Evaluation.
• Strong understanding of NLP, embeddings, vector search, and semantic retrieval.
Frameworks & Tools
• Python programming expertise.
• Experience with TensorFlow, PyTorch, Scikit-learn, LangChain, LlamaIndex, or
similar frameworks.
• Experience working with OpenAI, Anthropic, Gemini, Claude, Llama, Mistral, or
equivalent models.
RAG & Vector Databases
• Experience building production-grade RAG systems.
• Hands-on experience with vector databases such as Pinecone, Weaviate,
ChromaDB, Milvus, or FAISS.
• Knowledge of embedding models and retrieval strategies.
MLOps & Deployment
• Strong experience with MLOps practices and model lifecycle management.
• Experience with Docker, Kubernetes, CI/CD pipelines, and model monitoring.
• Expertise in deploying AI/ML solutions in production environments.
Cloud & Infrastructure
• Experience with AWS, Azure, or Google Cloud Platform (GCP).
• Understanding of scalable cloud-native architectures.
• Experience with REST APIs, microservices, and distributed systems.
Preferred Qualifications
• Experience leading AI/ML projects and mentoring engineering teams.
• Knowledge of AI governance, model security, and responsible AI practices.
• Exposure to multi-agent systems and autonomous AI workflows.
• Contributions to open-source AI projects or published research are a plus.
Educational Qualification
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data
Science, Machine Learning, or a related field. ",2026,Bachelors/Masters,5-10,"Python, ML, GenAI, LLMs, Prompt Engineering, NLP, VectorDb, RAG, TensorFlow/PyTorch, Scikit-Learn, Agents, LangChain, LangGraph, LlamaIndex, APIs, MLOps, CI/CD, Docker, Kubernetes, Git, Github, AWS/Azure, OpenAI","Communication, Problem Solving"
100,AI Engineer,Senior,"Success in this role requires:
• Mentoring and helping others to grow as engineers and developers
• Have excellent written and verbal communication skills
• Ability to excel in a distributed, remote team environment
• Self-drive to work on key initiatives
• Take pleasure in making things happen and listen to the input from peers
• Data-driven decision-making skills
• Embracing a best-idea-wins approach, regardless of the source
• Collaboration with cross-functional teams to define, design, and ship new features
• Staying current with emerging trends and technologies in AI and cloud computing
We are looking for:
• 10+ years of experience in building large-scale cloud-based distributed applications
• Strong experience in building multi-tenant SaaS applications
• Expertise with AI technologies, including LLM models, RAG, LangChain, and LlamaIndex
• Ability to design and develop scalable and robust AI-driven applications
• Excellent problem-solving, debugging, and analytical skills with great attention to detail
• Experience with microservices and cloud-based architectures/design patterns
• Demonstrated proficiency in English at the C1 level
Technical Skills:
• Extensive experience in Python and Java
• Proficient with NLP libraries and tools (spaCy, NLTK, Hugging Face Transformers)
• Skilled in model deployment frameworks (TensorFlow Serving, MLflow, Kubernetes-based deployments)
• Hands on Experience with ETL processes, data pipelines, and data warehousing solutions
• Expertise with top-tier datastores (MongoDB, AWS DocumentDB, SQL Server, MySQL)
• Proficient in Linux
• Experience with Apache Tomcat, Nginx, AWS, Docker, and Kubernetes
• Familiarity with CI/CD pipelines and tools (Jenkins, GitLab CI, CircleCI)
• Understanding of container orchestration tools and concepts
• Knowledge of security best practices in cloud and distributed applications
• Experience with infrastructure as code (IaC) tools (Terraform, CloudFormation). ",2026,Not Specified,15+,"Python, LLMs, RAG, Agents, LangChain, LangGraph, LlamaIndex, NLP, TensorFlow/PyTorch, ML, Github, Git, AWS/Azure, CI/CD, SQL, MLflow, MLOps, Docker, Kubernetes","Communication, Problem Solving, Analytical Skills"
103,AI Engineer,Senior,"• 7–12 years of overall software/AI engineering experience
• Strong hands‑on experience with AWS Bedrock in real projects (not PoC-only exposure)
• Proven experience building agentic AI or tool‑using LLM workflows
• Solid experience with Python for GenAI development
• Hands‑on experience with RAG architectures , embeddings, and vector stores
• Strong AWS fundamentals: IAM, networking basics, serverless services
• Clear understanding of GenAI risks, hallucination management, prompt controls
Good‑to‑Have Skills
• Experience with frameworks like LangChain, LlamaIndex, Semantic Kernel
• Exposure to enterprise domains such as BFSI, healthcare, insurance, or pharma
• Experience in model evaluation, benchmarking, and observability
• Prior experience working on customer-facing or production AI platforms
Mandatory Skills:
• Hands‑on AWS Bedrock implementation (real project experience, not learning/demo)
• Agentic AI / LLM agents / tool‑calling workflows
• RAG architectures + vector databases
• Strong Python background ",2026,Not Specified,5-10,"Python, AWS/Azure, LLMs, GenAI, RAG, VectorDB, LangChain, LangGraph, LlamaIndex, Agents","Communication, Problem Solving"
104,AI Engineer,Senior,"• 4+ yrs building AI-powered products served in production.
• Strong Python; production LLM/RAG; embeddings + vector databases (HNSW/IVF indexing).
• Inference serving (FastAPI/Triton/TorchServe-class); latency/throughput optimization.
• NLP fundamentals; API design; caching and queueing.
Strong signals
• Learning-to-rank / recommendation systems; multilingual/low-resource NLP; semantic search; on-device inference integration; prompt/reasoning orchestration. ",2026,Not Specified,1-5,"Python, LLMs, VectorDB, RAG, APIs, NLP","Communication, Problem Solving"
105,AI Engineer,Senior,"-5+ years of professional experience as a Fullstack Developer building production applications
-Strong hands‑on experience with Microsoft Azure (App Services, Azure Functions, APIs, storage, authentication, etc.)
-Solid backend development experience (e.g., .NET, Java, Node.js, or Python) with API and service‑oriented architectures
-Frontend development experience with modern frameworks (React, Angular, or similar)
-Experience working on cloud‑based or AI‑adjacent products, including integration with AI/ML services or data‑driven platforms ",2026,Not Specified,5-10,"Python, .NET, Java, Javascript, React, APIs, AWS/Azure, ML","Communication, Problem Solving"
106,AI Engineer,Senior,"• 9–12 years of overall experience with strong ML engineering focus
• Hands-on experience in ML and DL frameworks (TensorFlow / PyTorch / scikit-learn)
• Experience working with LLMs and GenAI architectures
• Strong Python programming skills
• Experience deploying models on AWS (SageMaker, EC2, Lambda, S3)
• Experience building REST APIs for model serving
• Strong understanding of data preprocessing and feature engineering ",2026,Not Specified,5-10,"Python. ML, TensorFlow/PyTorch, Scikit-Learn, LLMs, GenAI, AWS/Azure, APIs","Communication, Problem Solving"
111,AI Engineer,Senior,"• 5+ years of experience in Python-based application development.
• Hands-on experience building enterprise AI applications using LangGraph and LangChain.
• Experience integrating LLMs through AWS Bedrock.
• Strong knowledge of PostgreSQL and Snowflake.
• Experience designing scalable cloud-native applications on AWS.
• Excellent problem-solving and communication skills.
• Experience working in Agile/Scrum environments. ",2026,Not Specified,5-10,"Python, ML, LLMs, AWS/Azure, SQL, APIs, Agents, LangGraph, LangChain","Communication, Problem Solving"
167,AI Developer,Senior,"Required Skills & Qualifications :Technical Skills :- Strong hands-on experience in Python backend development.- Proven expertise with Agentic AI frameworks such as :i. LangGraphii. CrewAIiii. AutoGeniv. LangChain- Experience working with Model Context Protocol (MCP) tools and integrations.- Strong proficiency in FastAPI and modern API development.- Experience with cloud platforms :i. AWS (Bedrock preferred)ii. Microsoft Azure (AI Foundry preferred)- Hands-on experience with :i. Dockerii. Kubernetesiii. CI/CD pipelinesiv. Cloud security and governancePreferred Skills :- Experience with Retrieval-Augmented Generation (RAG) architectures.- Knowledge of vector databases and semantic search solutions.- Familiarity with observability, monitoring, and AI model evaluation frameworks.- Understanding of enterprise AI governance, security, and compliance requirements.Education :- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.- Any Graduate with relevant experience is welcome to apply. ",2026,Bachelors,5-10,"Python, Agents, LangChain, LangGraph, LlamaIndex, LLMs, ML, Pandas, RAG, MCP, APIs, AutoGen, CrewAI, Docker, Kubernetes, AWS/Azure, CI/CD, VectorDB","Communication, Problem Solving, Analytical Skills"
168,AI Developer,Senior,"Required Qualifications
• 3–6 years of software development experience, with solid hands-on experience in AI/ML or LLM application development.
• Strong proficiency in Python.
• Practical experience building APIs and backend services using FastAPI or a similar backend framework.
• Experience working with PostgreSQLor similar SQL/relational databases.
• Hands-on experience integrating LLMs into real applications.
• Goodunderstanding of prompt engineering, structured outputs, and retrieval-based workflows.
• Understanding of core AI/MLand data science concepts, including training data, model evaluation, embeddings, classification, and basic fine-tuning concepts.
• Exposure to model training or training support workflows, including data preparation and evaluation.
• Familiarity with backend integration patterns involving APIs, databases, async processing, and service-to-service communication.
• Ability to debug issues across prompts, model behavior, application logic, and data flow.
• Strong problem-solving skills and ability to work independently on implementation tasks.
Preferred Qualifications
• Experience with production use of OpenAI or comparable LLM platforms.
• Familiarity with embeddings, vector search, semantic retrieval, and RAG workflows.
• Experience with agent-style workflows, orchestration patterns, multi-step pipelines, or tool-calling systems.
• Awareness of recentAI ecosystem developments such as MCP, tools/skills patterns, and evolving agent integration approaches.
• Experience with batch jobs, background workers, schedulers, or queue-based processing.
• Familiarity with Docker and containerized deployments.
• Exposure to AWSor similar cloud platforms.
• Understanding ofAI observability, token usage, and cost-aware implementation.
• Experience contributing to technical design and solution planning ",2026,Bachelors/Masters,5-10,"Python, LLMs, ML, APIs, SQL, Prompt Engineering, VectorDB, OpenAI, MCP, Docker, AWS/Azure","Communication, Problem Solving"
169,AI Developer,Senior,"• Minimum 3 years of Creatio development experience including solution design and architecture on a production enterprise implementation

• Proficiency in C#, JavaScript and T-SQL, the core Creatio development stack

• Deep knowledge of Creatio business process designer, data model, section and detail customisation

• Experience with Creatio REST API and OData integration patterns

• Creatio Academy certification or demonstrable equivalent knowledge

AI platform: essential

• Python proficiency, data structures, API clients, async patterns, file handling

• Claude Code Must be demonstrated in the technical interview. You will use Claude Code daily to navigate codebases, diagnose issues, design solutions and implement features collaboratively with AI assistance

• GitHub mandatory. Branching strategy, pull requests, code review, issue tracking and collaborative development workflows.

• Familiarity with REST API design and OAuth 2.0 authentication flows

Nice to have

• Azure DevOps — pipeline configuration, resource management, deployment automation

• Experience with LLM API integration (Anthropic, OpenAI or equivalent)

• Plotly Dash or equivalent Python data visualisation framework

• Google Workspace API integration experience

• Microsoft 365 / Graph API integration experience 
",2026,Not Specified,5-10,"Python, SQL, Javascript, C#, APIs, Github, Git, LLMs, OpenAI, AWS/Azure","Communication, Problem Solving, Analytical Skills"
170,AI Developer,Senior,"• 3+ years of experience in Generative AI, AI Operations, Prompt Engineering, AI Evaluation, Product Operations, Business Analysis, Technical Writing, Content Strategy, or related fields.
• Strong understanding of Generative AI, Large Language Models (LLMs), and AI-powered applications.
• Hands-on experience with AI platforms such as ChatGPT, Claude, and Gemini.
• Experience creating and optimizing prompts for business or operational use cases.
• Strong analytical, problem-solving, and critical-thinking abilities.
• Excellent written and verbal communication skills.
• Ability to work independently in a remote environment.
Good to Have
• Experience with Retrieval-Augmented Generation (RAG) concepts and knowledge-based AI systems.
• Familiarity with AI agents, workflow automation tools, and no-code/low-code AI platforms.
• Experience with AI evaluation frameworks and RLHF (Reinforcement Learning from Human Feedback).
• Basic understanding of APIs, Python, SQL, or automation platforms.
• Experience working with AI training data, annotations, or model evaluation projects.
• Knowledge of AI governance, trust & safety, and responsible AI practices. ",2026,Not Specified,1-5,"Python, GenAI, ML, Prompt Engineering, LLMs, RAG, Agents, LangChain, LangGraph, APIs","Communication, Problem Solving"
171,AI Developer,Senior,"Required Technical SkillsProgramming Language
• Python
AI/ML Technologies
• Machine Learning and Artificial Intelligence
• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning
Frameworks & Libraries
• TensorFlow
• PyTorch
• Keras
• Scikit-learn
• Pandas
• NumPy
• Hugging Face
Deep Learning
• Neural Networks
• Convolutional Neural Networks (CNN)
• Recurrent Neural Networks (RNN)
Model Training FrameworksAnalytics & Monitoring
• ELK / Elastic Stack
Data Engineering
• Data ETL Tools
Development & Deployment
• Software Development Practices
• Containerization Technologies
• API Development and Integration
Experience
• 6 to 9 years of relevant experience in AI Development, Data Science, Machine Learning, and AI-based application development.
• Hands-on experience with Python and leading AI/ML frameworks.
• Experience in model training, evaluation, deployment, and optimization.
Qualification
• B.E./B.Tech/M.E./M.Tech/MCA/M.Sc. (Computer Science, Data Science, Artificial Intelligence, Information Technology, Mathematics, Statistics, or equivalent) from a recognized institute/university. ",2026,Bachelors/Masters,5-10,"Python, ML, TensorFlow/PyTorch, Scikit-Learn, Pandas, NumPy, Hugging Face, APIs, Docker","Communication, Problem Solving, Analytical Skills"
182,AI Developer,Senior,"Required Skills
• Strong proficiency in Python Programming.
• Experience with AI/ML libraries such as:
• NumPy
• Pandas
• Scikit-learn
• TensorFlow
• PyTorch
• Knowledge of Generative AI, LLMs, Prompt Engineering, and AI APIs.
• Experience with Django, Flask, or FastAPI.
• Strong understanding of databases (MySQL, PostgreSQL, MongoDB).
• Knowledge of Git and version control systems.
• Familiarity with cloud platforms is an advantage.
• Good communication, presentation, and mentoring skills.
Preferred Qualifications
• Bachelor's/Master's Degree in Computer Science, IT, Data Science, AI, or related field.
• Industry experience in AI/ML or Full Stack Development.
• Previous teaching or training experience is preferred.
• Relevant certifications in Python, AI, ML, or Data Science are an added advantage. ",2026,Bachelors/Masters,1-5,"Python, ML, NumPy, Pandas, Scikit-Learn, TensorFlow/PyTorch, GenAI, Prompt Engineering, LLMs, APIs, Django, SQL, Git, Github, AWS/Azure","Communication, Problem Solving"
187,AI Developer,Senior,"Agentic AIRetrieval Augmented GenerationMachine Learning
Artificial IntelligenceNatural Language ProcessingPython",2026,Bachelors,5-10,"Python, RAG, ML, NLP","Communication, Problem Solving"
188,AI Developer,Senior,"46 years of experience in machine learning and deep learning.
Strong proficiency in Python and ML frameworks like TensorFlow, PyTorch, Hugging Face Transformers.
Experience with LLMs, GANs, VAEs, or diffusion models.
Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps tools.
Understanding of NLP, computer vision, and multimodal AI systems.
Experience with model evaluation metrics and A/B testing.
Excellent problem-solving and communication skills.",2026,Bachelors,5-10,"Python, ML, TensorFlow/PyTorch, Hugging Face, LLMs, AWS/Azure, MLOps, NLP","Communication, Problem Solving"
189,AI Developer,Senior,"Expertise in Agentic AI, Generative AI development
Expertise in coding using python from a programming language perspective
Good work experience of ML models, LLM, Retrieval-Augmented Generation(RAG), Model
Context Protocol(MCP), Langchain, Langgraph etc.
Experienced in understanding functional requirement, integrate AI models with microservices/APIs, connect to databases
Experienced in using CI/CD tools like Github, Jenkins
Experienced in Agile project using Jira tool",2026,Bachelors,5-10,"Python, GenAI, Agent, LangChain, LangGraph, RAG, LLMs, ML, MCP, CI/CD, Github, Git","Communication, Problem Solving"
190,AI Developer,Senior,"3-5 years of experience in software development with hands-on experience implementing AI/ML or Generative AI solutions in production environments.
Strong understanding of AI technologies across the Software Development Lifecycle (SDLC), including AI coding assistants, AI-driven testing frameworks, and automation tools.
Experience with MLOps concepts, AI model deployment, monitoring, and lifecycle management.
Proficiency in one or more programming languages such as Python, Java, or .NET.
Strong knowledge of Generative AI, Large Language Models (LLMs), prompt engineering, and modern AI frameworks and tools.
Demonstrated ability to design and deliver AI Proof of Concepts that showcase technical feasibility and business impact.
Excellent communication and consulting skills with the ability to translate complex AI concepts into clear business value and ROI.
Experience working directly with clients and stakeholders to gather requirements, present AI solutions, and influence decision-making.
Strong analytical, problem-solving, collaboration, and stakeholder management skills.
Passion for continuous learning and driving AI innovation across engineering teams.",2026,Bachelors,1-5,"Python, ML, GenAI, MLOps, LLMs, Java, .NET, Prompt Engineering, ","Communication, Problem Solving"