Senior Engineer - Agentic AI, Assistant Manager
State Street4 days ago
Hyderābād, IndiaSenior
Responsibilities
- Design, develop, and integrate AI agents with enterprise APIs, applications, tools, data sources, knowledge repositories, and workflow services.
- Build reusable single-agent and multi-agent workflows with planning, routing, memory, state management, tool calling, retries, checkpointing, and failure recovery.
- Establish agent evaluation, observability, regression testing, execution tracing, quality metrics, and production monitoring.
- Implement human-in-the-loop approvals, guardrails, structured evaluation, responsible execution controls, and governance requirements.
- Configure and integrate AWS Bedrock Agents, Guardrails, foundation models, and equivalent cloud-native agent services.
- Package and deploy agent services using containers, serverless patterns, infrastructure as code, deployment pipelines, and enterprise cloud security controls.
- Design ontologies and knowledge graphs, including graph data modeling, ingestion, entity and relationship enrichment, lineage, provenance, and semantic validation.
- Build Python APIs and RAG or Graph RAG components for document processing, hybrid retrieval, graph traversal, grounding, source attribution, citations, testing, troubleshooting, and performance tuning.
- Apply data privacy, access control, auditability, model-risk, responsible-AI, and AI-governance practices through production support.
- Collaborate with architects, senior engineers, product owners, delivery teams, business stakeholders, and technology leaders.
Requirements
- Bachelor's degree in computer science, engineering, artificial intelligence, data science, information systems, or a related discipline; a master's degree is preferred but not required.
- 7 to 12 years of overall technology experience in software engineering, data engineering, AI engineering, knowledge engineering, or enterprise platform development.
- At least 3 years of hands-on experience developing or supporting enterprise data, semantic, graph, search, knowledge, or AI solutions.
- Experience developing or integrating AI agents with enterprise APIs, tools, data sources, knowledge repositories, and workflow services.
- Experience with agent frameworks such as LangChain, LangGraph, LlamaIndex, or Semantic Kernel; experience with LangSmith and AI evaluation tools is also required.
- Experience with agent orchestration, tool or function calling, agent memory, planning, routing, state management, guardrails, human-in-the-loop controls, and structured evaluation.
- Experience with AWS Bedrock Agents, Guardrails, foundation-model integrations, or equivalent cloud-native agent services.
- Experience with containerization, serverless deployment, infrastructure as code, deployment practices, monitoring, troubleshooting, and enterprise cloud security patterns.
- Knowledge of responsible AI, data privacy, access controls, auditability, model risk, and AI governance in regulated environments.
- Preferred experience with enterprise graph platforms such as Neo4j, Amazon Neptune, or GraphDB, and with Cypher or SPARQL.
- Preferred experience designing ontologies, semantic models, metadata structures, taxonomies, entity types, relationship definitions, ingestion pipelines, RAG, Graph RAG, hybrid retrieval, reranking, groundedness testing, and graph enrichment.
- Strong Python programming skills, including REST API or microservice development, error handling, automated testing, and production-quality code.
- Knowledge of RDF, RDFS, OWL, SHACL, labeled property graphs, knowledge representation, and semantic validation techniques.
- Strong analytical, problem-solving, documentation, communication, presentation, ownership, and cross-functional collaboration skills.
- Proven experience delivering Knowledge Graph, Ontology, RAG, Graph RAG, Agentic AI, or Generative AI solutions from design through production implementation.
Benefits
- Flexible work-life support, paid volunteer days, inclusive development opportunities, and employee networks.
- The role is part of a global team operating across North America, EMEA, and APAC.
- Work focuses on real client implementations that are adopted, measured, and scaled.
Categories
About State Street
State Street is a global custodian bank and asset manager serving institutional investors with investment servicing, fund accounting, trading/FX, data, and index/active strategies. Its products include State Street Global Advisors’ funds and ETFs, the Charles River Investment Management Solution, and the front-to-back State Street Alpha platform. Founded in 1792 and headquartered in Boston, the company is publicly traded on the NYSE (ticker: STT) and operates across major markets worldwide.