multiple_docs/ai_engineering.txt

AI engineering experience:

Founder & AI Engineer, Plaidoyer.ai, London, 01/2026 to present 
I built a software platform that helps French lawyers quickly find legal information, manage case documents 
securely, and use AI to assist with research and client communication, ensuring full privacy compliance. 
Responsibilities: 
- Developed hybrid retrieval pipeline using PostgreSQL pgvector and HNSW indexing for 2.9M+ French legal 
documents 
- Implemented semantic search with BGE-M3 embeddings and full-text search capabilities 
- Integrated cross-encoder reranking and HyDE query expansion for improved search accuracy 
- Designed LLM-based query requalification with conversational clarification loop 
- Built RAG assistant for document chat with strict tenant isolation and prompt-injection defenses 
- Engineered data ingestion pipeline from LegiFrance/DILA APIs with rate-limited batch extraction 
- Architected compliance-first LLM system ensuring EU-only inference and zero data retention 
- Developed backend with FastAPI, SQLAlchemy, and Alembic + frontend using React and TypeScript 
- Deployed and managed infrastructure on Hetzner and AWS platforms (Python, AWS, Docker, Linux, Alembic, 
HNSW, TypeScript, SQLAlchemy, Hetzner, LLM, FastAPI, React, Amazon S3, JWT, Mistral AI, Rag, BGE-M3, 
PostgreSQL, Pgvector)