Core Data -AI Enablement Engineer - Assistant Manager

State Street — Bangalore, India

Our technology function, Global Technology Services (GTS), is vital to State Street and is the key enabler for our business to deliver data and insights to our clients. We’re driving the company’s digital transformation and expanding business capabilities using industry best practices and advanced technologies such as cloud, artificial intelligence and robotics process automation. We are seeking a motivated and enthusiastic AI Enablement Engineer to join our team and contribute to the development and integration of cutting-edge AI solutions into our business processes. This is a highly technical and hands-on role where you will work closely with senior team members to build AI systems leveraging technologies such as Generative AI (Gen AI), Retrieval-Augmented Generation (RAG), Agentic AI frameworks (LangChain, LangGraph), Graph-based systems and Large Language Models (LLMs). You will collaborate closely with software engineers and investment servicing business teams to solve complex business challenges in the asset servicing domain. Role Description: - Develop and maintain AI agent pipelines using LangChain and LangGraph, including ReAct agents, tool-calling workflows, stateful graph execution and SSE streaming responses. - Build and extend RAG pipelines for knowledge-intensive tasks — document ingestion, chunking, embeddings, vector search and LLM-based generation. - Integrate AI agents with Snowflake, Azure Blob Storage, PostgreSQL and REST APIs to support end-to-end data workflows. - Design prompt engineering strategies (ReAct, CoT, structured output, few-shot) for LLMs such as Azure OpenAI. - Build and expose agent capabilities via FastAPI and contribute to backend services in Python. - Optimize agent pipelines for performance, reliability and scalability in a cloud (Azure) environment. - Track, version and manage AI/LLM experiments using MLflow — including logging parameters, metrics, prompts and model artifacts for reproducibility and comparison. - Collaborate

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