GenAI / RAG Engineer

Experience: 6+ years (4+ years hands-on in GenAI/LLM applications)

Location: Chennai / Gurgaon

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3. Lack of seriousness or commitment? Give way to candidates genuinely interested in long‑term growth and contribution please!

What you'll build

Design, build, and scale production-grade AI systems for enterprise document intelligence and conversational analytics. The role involves building retrieval pipelines, multi-agent workflows, and production safeguards that ensure accurate, explainable, and reliable AI outputs in high-stakes enterprise contexts.

What you'll own

- End-to-end RAG pipelines: ingestion, chunking, embeddings,



hybrid retrieval, and reranking
- Multi-agent workflows for validation, routing, and human-in-the-loop review
- Natural-language-to-query for analytics over enterprise data
- Failure handling: detecting low-confidence or no-match retrieval and escalating instead of hallucinating
- Evaluation (precision/recall, faithfulness, groundedness) on real annotated data

Must have

- Python, FastAPI, REST APIs
- RAG in production, not just POCs
- Azure AI Search, AWS OpenSearch, or equivalent
- LangChain/LangGraph or similar orchestration
- Experience with enterprise documents

Valuable to have

- Document comparison or analysis systems
- Human-in-the-loop and escalation design
- LLM cost and latency optimization

📌 Generative AI Engineer (Chennai)
🏢 Infotech Global
📍 Chennai