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Open nowPosted today

Artificial Intelligence & Machine Learning, AVP

State Street1,064 open roles

Where
Hangzhou, China
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Your applicationOpen nowArtificial Intelligence & Machine Learning, AVPState Street · Hangzhou, China

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The clock on this job

Early applications get read.

13.3% of postings close within 7 days. Measured by our own scanner across the market. State Street postings stay open a median of 31 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.6%3 days
  3. 13.3%7 days
  4. 21.3%14 days
  5. 35.7%30 days
  6. 59.1%60 days
This job: posted today

State Street median: 31 days open

The posting

A highly experienced, hands-on technology leader to serve as Principal Agentic AI Engineer. This role will report to the AI Platform leadership team and will define the target-state Agentic AI platform architecture, establish engineering standards, and guide the delivery and adoption of strategic agentic AI solutions across the organization.

Why this role is important to us

Agentic AI is transforming how organizations automate knowledge-intensive work, accelerate decision-making, and unlock value from enterprise data. Realizing this opportunity at scale requires a secure, governed, and reusable platform that enables engineering and business teams to build production-ready AI solutions. The Principal Agentic AI Engineer will shape this platform, set its technical direction, and ensure that it supports investment performance, investment research, data operations, and related daily operations.

What you will be responsible for

In this role, you will:

  • 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.

What we value

These skills will help you succeed in this role:

  • 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.

Education & Preferred Qualifications

  • 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.
  • Experience in financial services, investment management, or another large-scale regulated enterprise is preferred.

Additional Requirements

  • 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.
  • Relevant cloud, architecture, data, or AI certifications are a plus but not required.

About State Street

Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.

We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.

As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.

Discover more information on jobs at StateStreet.com/careers

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