AI Engineer ( Generative AI / RAG )

Xminds Infotech Pvt Ltd; Thiruvananthapuram; On-site; INR 1,500,000 - 2,200,000; Full time

Job summary

Xminds Infotech Pvt Ltd is hiring an AI Engineer to build production generative-AI applications for enterprise clients. You will develop RAG pipelines, prompts, LLM integrations and content guardrails within a small delivery team under a Solution Architect.

You will implement multilingual prompts, model routing swaps, content-safety checks and explainability signals, while evaluating models and monitoring latency and cost in a collaborative environment with backend, frontend and DevOps teams.

Qualifications

• 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 vector databases (pgvector, Azure AI Search, Pinecone, Qdrant, Weaviate).
• LangChain or LangGraph (or LlamaIndex / similar).
• FastAPI, PostgreSQL, Docker; Git.
• Any major cloud (Azure preferred).

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.

Skills

Python

LLM in production

RAG fundamentals

LangChain

FastAPI

PostgreSQL

Docker

Git

Azure preferred

Vector databases

Education

Bachelor's in Computer Science or related field

Tools

Docker

FastAPI

PostgreSQL

Git

Job description

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.

Disclaimer: This job posting and location 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.