S

State Street

Holds assets for institutions and runs index funds

Principal Agentic AI Engineer

Natural Language Processing & LLMsPosted on Nov 11
Full-timeHangzhou, Zhejiang, ChinaNo salary listedIn-person

About the Job

Requirements

  • Strong strategic and systems-thinking skills, with sound judgment across innovation, scalability, reliability, cost, security, and governance.
  • Ability to translate business objectives into practical platform capabilities and executable technical roadmaps.
  • Ability to influence engineering teams, architects, governance functions, and senior stakeholders without relying solely on formal authority.
  • Clear and effective communication, including the ability to explain complex AI and data concepts to technical and non-technical audiences.
  • A hands-on, delivery-oriented mindset with strong ownership, curiosity, and commitment to engineering quality.
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Data Engineering, or a related discipline.
  • 10+ years of experience in software engineering, platform engineering, data engineering, solution architecture, or related technology roles.
  • Proven experience owning or leading enterprise-scale Agentic AI or Generative AI architecture and delivery.
  • Deep knowledge of agent orchestration, planning, memory, tool calling, evaluation, guardrails, multi-agent systems, and human-in-the-loop design.
  • Hands-on experience with agent frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, Google ADK, or comparable technologies.
  • Strong experience with Python, APIs, microservices, distributed systems, event-driven design, and cloud-native engineering.
  • Experience designing RAG and enterprise knowledge solutions using vector databases, knowledge graphs, ontologies, metadata, and hybrid retrieval.
  • Experience with distributed data platforms and technologies such as Apache Spark, Apache Iceberg, Databricks, Kafka, Delta Lake, Snowflake, or comparable platforms.
  • Experience architecting platforms and AI solutions on AWS, Google Cloud Platform, and/or Microsoft Azure.
  • Solid understanding of Kubernetes, containers, infrastructure as code, CI/CD, observability, security architecture, data governance, and metadata management.
  • Demonstrated ability to operate as an AI-augmented architect, using GenAI tools to accelerate solution design, software development, documentation, and decision-making while maintaining architectural judgment and quality standards.
  • Knowledge of Responsible AI, AI governance, model risk, AgentOps, LLMOps, and production support practices.
  • Ability to lead complex technical initiatives across organizational and geographic boundaries.

Responsibilities

  • Define and own the end-to-end target-state architecture for the Agentic AI platform, including prompt engineering, agent orchestration, memory, tool integration, knowledge management, multi-agent collaboration, and human-in-the-loop patterns.
  • Lead the design and implementation of strategic, production-grade agentic AI solutions for investment performance, investment research, data operations, and related business workflows.
  • Establish architectural principles, engineering standards, reusable patterns, and guardrails for agentic AI development and adoption.
  • Define architectural standards for an Iceberg-based Lakehouse, including table design, partitioning, schema evolution, metadata, performance, and lifecycle management.
  • Design enterprise knowledge capabilities using retrieval-augmented generation, vector search, knowledge graphs, ontologies, metadata, and semantic retrieval.
  • Review platform, data, and solution designs to ensure alignment with architectural principles, performance expectations, security requirements, and enterprise standards.
  • Partner with Platform Engineering to align infrastructure, identity and access management, security, observability, CI/CD, AgentOps, and LLMOps capabilities with architectural intent.
  • Work with Enterprise Architecture, Governance, Risk, and Security teams to meet access-control, Responsible AI, compliance, and audit requirements.
  • Publish and maintain reference architectures, design guidelines, engineering patterns, and architectural decision records.
  • Identify architectural risks, technical debt, and improvement opportunities, and guide the evolution of the platform over time.
  • Mentor senior engineers and influence technical direction across multiple engineering and application teams.

Desired Qualifications

  • Experience in financial services, investment management, or another large-scale regulated enterprise is preferred.
  • Relevant cloud, architecture, data, or AI certifications are a plus but not required.

About the Company

State Street

Holds assets for institutions and runs index funds

State Street holds and services investments for pension funds, insurers, fund companies, and other large institutions, and it also runs index funds through State Street Investment Management. It launched the first US-listed exchange-traded fund, the SPDR S&P 500 ETF Trust, in 1993, and in 1924 it became custodian of the first US mutual fund. As a custody bank, it safekeeps clients' stocks and bonds, completes their trades, calculates what their funds are worth, and lends their securities to other investors. It earns fees on the assets it services and manages, plus income from currency trading and from interest on client cash. State Street traces its roots to a bank chartered in 1792 and is based in Boston, Massachusetts.

Company size
10,001+
Company stage
IPO
Headquarters
Boston, MA
Founded
1792

Recently Posted Jobs

Explore more opportunities at State Street

See more jobs