Experience :

- 6-10+ years in software engineering
- 4+ years in GenAI / NLP / LLM-based systems
- Proven experience building production-grade AI systems

Key Responsibilities

- Design and build RAG pipelines (ingestion indexing retrieval generation)

- Develop data ingestion pipelines:

- Document upload (PDF, DOCX, PPT)

- Parsing, table extraction, image extraction

- Image captioning & semantic chunking

- Metadata tagging & versioning

- Implement hybrid search (vector + keyword + optional graph)

- Build APIs using FastAPI (Python) for chat and orchestration

- Integrate LLMs (OpenAI / Claude via AWS Bedrock)

- Optimize response accuracy, latency, and cost

- Implement evaluation & observability (RAGAS, Langfuse/LangSmith)

Tech Stack

- Languages/Backend: Python, FastAPI
- LLM & Frameworks: LangChain, LangGraph, CrewAI
- Cloud: AWS (S3, ECS/Fargate, Lambda,



API Gateway, Bedrock)
- Databases: Any Vector DB
- Data Ingestion: Unstructured, PyMuPDF, Tesseract, custom pipelines
- DevOps: Docker, GitHub Actions
- Observability/Eval: Langfuse, LangSmith, RAGAS, DeepEval

Requirements :

- 6+ years in software engineering, strong in Python
- Hands-on experience with LLMs & RAG systems
- Experience building data ingestion pipelines and search systems
- Valuable understanding of embeddings, semantic search, and prompt engineering
- Experience with cloud deployment (AWS preferred)

Nice to Have

- Multi-modal RAG (images, tables)
- Agentic AI workflows (LangGraph / ReAct patterns)
- Experience with enterprise AI systems

📌 Ai/ml Engineer (Vit/hr/aimle/15/0526) (Pune)
🏢 Vidushi Infotech
📍 Pune