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