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Global Head of Analytics and AI Platform Engineering, Managing Director

State Street

Hangzhou, China

AI Infrastructure

Posted 13 days ago

vponsite

Verified open on Sep 16, 2026 · posted 12 days ago

Job Description

Who we are looking for

State Street Investment Management (SSIM)—formerly State Street Global Advisors (SSGA)—is seeking an accomplished senior leader to serve as the Global Head of Analytics and AI Platform Engineering. This Managing Director role is critical to shaping, driving, and executing the Analytics and AI strategy that underpins the Investment Management division’s transformation.

As a strategic partner to the Global Head of Data, Analytics, and AI Services (DAAIS), you will oversee advanced analytics and AI infrastructure and platform services supporting the COO organization across SSIM globally. You will lead global teams responsible for platform engineering, software engineering, ML/LLM Ops, FinOps, tools and framework provision related to analytics, AI/ML/DL, Generative AI, and Agentic AI—ensuring alignment with GTS standards and the target Analytics and AI ecosystem blueprint.

What’s the Value for you

This is a senior global role requiring deep expertise in analytics and AI infrastructure architecture, platform engineering, governance, and modern ML/GenAI/Agentic AI development, combined with significant leadership experience in asset management.

What you will be responsible for

Leadership & Strategy

  • Support SSIM’s Analytics and AI vision and strategy; lead end‑to‑end implementation of platform infrastructure, software application, foundational data science capabilities, advanced analytics and AI frameworks, tooling, ML/LLM Ops, and Model Observability.
  • Lead and mentor high‑performing engineering teams across the US, China, India, and Poland—building a culture grounded in deep technology expertise and accountability (not traditional staff‑augmentation models).
  • Define SSIM’s Analytics and AI Platform architecture, establish engineering standards, and guide implementation and governance practices.
  • Ensure a modular, scalable, and reusable architecture to eliminate siloed development and accelerate time to market.
  • Champion engineering excellence, technical rigor, and innovation across the organization.

Engineering Excellence

  • Innovation & Best Practices: Evaluate, adopt, and standardize cutting‑edge technology capabilities—including IAC, Cloud Computing/Agnostic, GPU/TPU/FPGA/CUDA, AI frameworks, GenAI/Agentic AI integration protocols/frameworks, distributed computing, and HADR.
  • Quality & Performance: Ensure solutions meet the highest engineering standards through code reviews, testing frameworks, and adherence to industry guidelines.
  • Collaboration & Mentorship: Build a collaborative engineering community focused on continuous learning, knowledge sharing, and professional development.
  • Scalability & Resilience: Architect systems capable of supporting global business workloads with strong reliability and performance characteristics.
  • Security & Compliance: Uphold stringent risk, security, and regulatory requirements; ensure robust data protection and governance.

Execution & Oversight

  • Lead global analytics and AI platform engineering teams with a focus on innovation, delivery excellence, and operating leverage.
  • Manage major vendor relationships—including analytics and AI platform providers and service partners—ensuring strong integration, service quality, and contractual outcomes.
  • Oversee the full analytics and AI business capability deployment required environment from sandbox, development, QA/UAT, production, to disaster recovery across a diverse set of use cases and global users

Education & Preferred Qualifications

  • Master’s degree required (Computer Science, Electrical Engineering or related field)
  • 15+ years in core engineering role at large enterprise ideally asset management industry.
  • 15+ years hands‑on engineering experience with a strong track record delivering analytics and/or AI solutions and platforms.
  • Proven experience leading global technology organizations across infrastructure, IAC, ML/LLM Ops, analytics and AI frameworks/tools, FinOps, high availability and disaster recovery, with strong delivery execution.
  • Strong understanding of the analytics and AI vendor landscape and demonstrated experience adopting vendor products and open‑source frameworks to improve scale and growth.
  • Exceptional leadership, stakeholder management, communication, and relationship‑building skills.
  • Fluent in English; highly detail‑oriented, results‑driven, candid, and execution‑focused.

Highly Preferred

  • Prior AI platform engineering leadership experience in large financial institution.
  • CFA Level I or equivalent credential.

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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Career context

This role is classified as AI Infrastructure - see the AI Infrastructure hub for the rest of the market.

$213k - $286k is the middle 50% of disclosed salaries, measured from 205 live AI Infrastructure postings on this board. Roughly two thirds of postings disclose nothing, so this describes the ones that do, not the whole market.

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