Job Summary

Design and build production retrieval-augmented generation systems that answer questions from enterprise content accurately and securely.

What you'll do

- Design RAG pipelines: ingestion, parsing, chunking, embeddings and hybrid search
- Implement permission-aware retrieval and metadata filtering
- Build evaluation sets and measure retrieval and answer quality
- Optimise latency and cost; implement caching and model routing
- Deploy and monitor RAG services in the cloud
- Mentor junior engineers

What you'll bring

- 3-6 years of software engineering experience, including at least 1-2 years with LLM applications
- Solid Python and API development skills
- Hands-on experience with vector databases and embeddings
- Experience with at least one of Amazon Bedrock, Azure OpenAI or Vertex AI
- Understanding of evaluation methods for LLM and RAG systems

Nice to have





- Experience with Azure AI Search, OpenSearch or pgvector at scale
- LLMOps and tracing tools (Langfuse, LangSmith)
- Document AI (Textract, Document Intelligence)

Tech stack

- Python
- LangChain / LlamaIndex
- Amazon Bedrock
- Azure OpenAI
- pgvector
- OpenSearch
- Azure AI Search
- FastAPI
- Docker
- Kubernetes

Location

Hyderabad, Telangana, India

Work authorization

Must be eligible to work in India

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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