AI Engineer (Generative AI / RAG)
Xminds Infotech (P) Ltd - Technopark (confirm workplace)
Apply by 2026-10-31
About the role
We are hiring an AI Engineer to build production generative-AI applications for our enterprise clients. You will build RAG pipelines, prompts, LLM integrations and content guardrails as part of a small delivery team under a Solution Architect. Key Responsibilities Build RAG pipelines: chunking, embeddings, hybrid retrieval and custom ranking. Write and maintain prompts and structured outputs for multilingual content generation. Integrate LLMs behind a routing layer that allows model swaps without code changes. Implement content guardrails: prohibited terms, policy rules, content-safety checks and approval workflows. Build explainability output — retrieved sources and confidence signals for each generation. Run model evaluations and A/B comparisons; track quality, latency and token cost. Work with backend, frontend and DevOps engineers; document what you build. Required Skills 4+ years Python; 2–3+ years building LLM applications in production. RAG fundamentals: embeddings, vector search, hybrid retrieval, chunking, evaluation. Experience with any LLM API (Azure OpenAI, OpenAI, Anthropic, Gemini). Experience with any vector database (pgvector, Azure AI Search, Pinecone, Qdrant, Weaviate). LangChain or LangGraph (or LlamaIndex / similar). FastAPI, PostgreSQL, Docker; Git. Any major cloud (Azure preferred). Preferred Skills Multilingual NLP exposure. Content-safety / guardrail tooling (Azure AI Content Safety, Guardrails AI). LLM evaluation tools (RAGAS, DeepEval, promptfoo) and observability (Langfuse, LangSmith, App Insights). Fine-tuning experience (LoRA / Hugging Face). Azure AI-102 or equivalent certification. Qualifications Bachelor's in Computer Science or related field. Clear communication and ability to work in a client-facing delivery team.
Requirements
- Multilingual NLP exposure.
- Content-safety / guardrail tooling (Azure AI Content Safety
- Guardrails AI).
- LLM evaluation tools (RAGAS
- DeepEval
- promptfoo) and observability (Langfuse
- LangSmith
- App Insights).
- Fine-tuning experience (LoRA / Hugging Face).
- Azure AI-102 or equivalent certification.
- Qualifications
- Bachelor's in Computer Science or related field.
- Clear communication and ability to work in a client-facing delivery team.