Role description

Senior AI Engineer (GenAI + Data Platform - AWS)

Role Summary

We are seeking a Senior AI Engineer to build and scale a production-grade GenAI and data platform on AWS, enabling LLM-powered capabilities through vector search, graph databases, and governed data pipelines.

This role owns end-to-end delivery across the AI lifecycle from data ingestion and knowledge curation embeddings and retrieval systems backend services and APIs CI/CD and deployment. You will partner closely with product and engineering teams to operationalize AI capabilities in externally facing applications.

This position also plays a key role in building and evolving our platform toward agentic systems, including implementing tooling, memory, state management, and guardrails, with all future enhancements and capabilities designed and delivered by our team.

Key Responsibilities

GenAI Enablement & Integration
- Enable LLM-powered use cases using patterns such as retrieval-augmented generation (RAG), embeddings pipelines, prompt orchestration, and evaluation strategies.




- Design and implement vector-based retrieval systems using Amazon OpenSearch (vector capabilities).
- Build and maintain graph-based knowledge systems using Amazon Neptune to support entity relationships, lineage, and explainability.
- Integrate supporting infrastructure:
- - Amazon ElastiCache (Redis) for low-latency caching and session state
- DynamoDB for high-scale, low-latency data access patterns
- Implement and operate production-grade LLM workflows and agentic patterns using frameworks such as LangGraph, AutoGen, or CrewAI (or equivalent).
- Integrate LLM application frameworks such as LangChain and/or LlamaIndex, including tool calling, retrieval orchestration, and context management.
- Establish standards for tool integration and context-sharing patterns (e.g., Model Context Protocol (MCP)-style designs), preparing the platform for Agent Core adoption.
- Evaluate and compare LLMs and retrieval strate

📌 ML Engineer I-CG (Pune)
🏢 UST
📍 Pune