Core Data -AI Enablement Engineer - Assistant Manager
State StreetResponsibilities
- Develop and maintain LangChain and LangGraph AI agent pipelines, including ReAct agents, tool-calling workflows, stateful graph execution, checkpointing, human-in-the-loop patterns, and SSE streaming responses.
- Build RAG pipelines covering document ingestion, chunking, embeddings, vector search, retrieval, and LLM-based generation.
- Integrate AI agents with Snowflake, Azure Blob Storage, PostgreSQL, REST APIs, and other external data and storage systems.
- Design prompt-engineering strategies for LLMs, including ReAct, chain-of-thought, structured output, and few-shot prompting.
- Build and expose AI agent capabilities through FastAPI and contribute to Python backend services.
- Optimize agent pipelines for performance, reliability, scalability, and cloud deployment in Azure.
- Track and version AI/LLM experiments, prompts, metrics, and model artifacts using MLflow.
- Identify AI use cases, translate business requirements into agent-based solutions, and collaborate with software engineers and asset-servicing business teams.
- Evaluate AI output quality, RAG performance, and agent benchmarking results using appropriate metrics and evaluation frameworks.
- Ensure AI solutions follow responsible AI principles and financial-services standards.
Requirements
- At least 8 years of professional experience.
- Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field.
- Proficiency in Python and solid software engineering fundamentals.
- Hands-on experience with LangChain, including chains, agents, ReAct, tool calling, LCEL, memory, retrievers, and document loaders.
- Hands-on experience with LangGraph, including StateGraph, stateful orchestration, conditional edges, checkpointing, and human-in-the-loop patterns.
- Strong understanding of RAG, chunking strategies, embedding models, vector stores, and retrieval-augmented generation.
- Experience with Azure OpenAI Service and LLM prompt-engineering techniques.
- Familiarity with FastAPI for building and exposing AI agent APIs.
- Knowledge of vector databases such as FAISS, Chroma, or Azure AI Search and experience with semantic search.
- Experience integrating LLMs with databases, APIs, and storage systems such as Snowflake and Azure Blob Storage.
- Experience evaluating AI applications, including LLM output quality, RAG evaluation metrics, agent benchmarking, and frameworks such as RAGAS, LangSmith Evals, or Azure AI Evaluation SDK.
- Strong communication skills and the ability to explain AI concepts to non-technical stakeholders.
- Preferred experience with MLflow, LangSmith, LangFuse, Docker, Kubernetes, AutoGen, CrewAI, or LlamaIndex.
- Preferred understanding of responsible AI principles and output guardrails.
Benefits
- Collaborative global technology environment with opportunities to develop technical skills and deliver innovative financial-services solutions.
- Inclusive development opportunities, flexible work-life support, paid volunteer days, and employee networks.
About State Street
At State Street, we deliver leading investment platforms, data, expertise, and solutions that accelerate performance and better decision making. With over 200 years of global financial leadership, we equip institutional investors through a comprehensive suite of capabilities: Investment Services: Integrated front-to-back solutions across custody, accounting, and operations. Investment Management: Index and active strategies from one of the world’s largest asset managers. Markets: Multi-asset trading, FX solutions, and data-driven research to enhance portfolio value. Who We Are • 50,000+ employees worldwide • Active in 100+ markets • #1 in ETF servicing What You’ll Find Here • Executive perspectives and thought leadership • Timely market commentary and macro insights • Our views on investment operations, ETFs, private markets, and digital finance • Stories reflecting our culture, values and commitment to diversity and inclusion