Analytics and AI Platform Engineering, Senior Principal, VP

Who we are looking for

State Street Investment Management (SSIM)—formerly State Street Global Advisors (SSGA)—is seeking an experienced leader to serve as the Analytics and AI Platform Engineering, Senior Principal. This Vice President role is important to shaping, driving, and executing the Analytics and AI strategy that underpins the Investment Management division’s transformation.

As a key player within the Global Head of Data, Analytics, and AI Services (DAAIS) organization, you will be leading advanced analytics and AI platform engineering work including design, development, integration, testing, and rollout solutions for all environments supporting the COO organization across SSIM globally. You will lead an engineering team 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 AI ecosystem blueprint.
 

What’s the Value for you

This is a senior engineering role requiring deep expertise in AI architecture, enterprise platforms, AI governance, and modern ML/GenAI development, combined with team leadership experience in asset management.

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What you will be responsible for

• Lead implementation of platform infrastructure, software engineering, foundational data science capabilities, advanced analytics and AI frameworks, tooling, ML/LLM Ops, and Model Observability.
• Lead and mentor a local high‑performing engineering team —building a culture grounded in deep technology expertise and accountability (not traditional staff‑augmentation models).
• Design SSIM’s Analytics and AI Platform architecture, implement engineering standards, and governance practices.
• Implement 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.

• Innovation & Best Practices: Evaluate, adopt, and standardize cutting‑edge analytics and AI capabilities—including Agentic AI, Generative AI, and foundational AI/ML/DL models.
• 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.

• Lead a local analytics and AI platform engineering team with a focus on innovation, delivery excellence, and operating leverage.
• Work with major vendors—including analytics and AI platform providers and service partners—ensuring strong integration, service quality, and contractual outcomes.
• Deliver the full analytics and AI 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)
• 13+ years in core engineering role at large enterprise ideally asset management industry.
• 12+ years hands‑on engineering experience with a strong track record delivering analytics and/or AI solutions and platforms in public cloud Azure and/or AWS using infrastructure as code programming and familiar with foundational AI/ML/DL, Generative AI and Agentic AI, Azure Active Directory based service principals, and managed identities provision automation.
• 10+ years of modern containerized, object-oriented or script programming experience like Python, Java, Shell etc.
• 8+ years of experience in microservice architecture and implementation based on main-stream technologies such as Kubernetes, Docker, Spring Cloud, gRPC/thrift etc.
• Familiar with structured and unstructured data storage and management systems like Snowflake, Databricks, PostgreSQL, and various vectorized databases.
• Familiar with source code management e.g. GitHub and CI/CD best practices to support concurrent development and release for multiple global teams.
• Fluent in English; highly detail‑oriented, results‑driven, candid, and execution‑focused.

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

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.

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