Job Description

Who we are looking for

Design, build, and operate enterprise AI platforms at scale, enabling secure, scalable, and high-performance capabilities across Traditional AI/ML, Generative AI, and Agentic AI—using modern engineering, Agile, and Site Reliability Engineering (SRE) practices.

The Head of AI Platform Engineering is accountable for delivering and operating enterprise-grade AI platforms that enable State Street to develop, deploy, and scale AI capabilities across all businesses and functions.

This is a deep engineering leadership role, leading a global organization of 100+ engineers to build and run AI platforms spanning:

• Machine Learning (ML)
• Generative AI (LLMs and foundation models)
• Agentic AI systems and orchestration frameworks

The role combines:

• Advanced AI/ML and distributed systems engineering
• Platform product mindset (platforms as reusable services)
• SRE discipline (reliability, observability, scalability)
• Agile execution (rapid iteration and continuous delivery)

The role works in close partnership with:

• Data Platform Engineering to leverage AI-ready data foundations
• Data Architecture to align with enterprise data models and structures
• Data & AI Strategy, Portfolio & Value to align with enterprise priorities and roadmap
• Responsible Data, AI Governance & Risk to ensure compliant and responsible usage

This leader is central to enabling a scalable, reusable AI ecosystem across Investment Services, Investment Management, Wealth, Alpha, Global Markets, and control functions.

Success is measured by platform adoption, engineering quality, scalability, performance, and the ability to accelerate AI innovation across the enterprise

What you will be responsible for

Enterprise AI Platform Engineering

• Design, build, and operate AI platforms as enterprise products, including:
  • ML development, training, and inference platforms
  • Generative AI platforms (LLM integration, orchestration, prompt systems)
  • Agentic AI frameworks and runtime environments
• Own the full lifecycle:
  • Platform engineering and development
  • Deployment and operations
  • Continuous optimization and evolution

Large-Scale Engineering Leadership (100+ Organization)

• Lead a global organization of 100+ engineers across:
  • AI/ML platform engineering
  • LLM and GenAI engineering
  • Agentic AI and workflow orchestration
  • Platform reliability engineering
• Build strong leadership layers and domain-aligned teams
• Drive a culture of:
  • Engineering excellence
  • Innovation with discipline
  • Ownership and accountability

Site Reliability Engineering (SRE) & AI Platform Operations

• Establish and embed SRE practices across AI platforms:
  • SLAs, SLOs, and error budgets
  • Observability across models and pipelines
  • Incident management and operational playbooks
• Ensure production-grade reliability for:
  • Model training and inference
  • API-based AI services
  • Agent-based systems
• Automate monitoring, scaling, and recovery for AI workloads

Agile Delivery & Platform Product Mindset

• Implement modern Agile and product-centric engineering practices
• Manage platforms as products, including:
  • Roadmap alignment with enterprise strategy
  • Continuous delivery and iteration
  • Feedback loops from users (engineers, data scientists, product teams)
• Drive disciplined execution through:
  • Backlog prioritization
  • Sprint-based delivery
  • Outcome-based measurement

AI/ML, GenAI & Agentic AI Platform Capabilities

• Deliver and evolve platforms across:
  • ML platforms (experimentation, training, deployment, feature pipelines)
  • Generative AI platforms (LLM orchestration, prompt management, evaluation)
  • Agentic AI platforms (multi-agent systems, task orchestration, automation workflows)
• Support both:
  • Centralized enterprise capabilities
  • Domain-specific customization

Integration with Data Platforms

• Leverage enterprise data platforms to enable:
  • High-quality training datasets
  • Feature engineering pipelines
  • Access to structured and unstructured data
• Ensure tight integration of:
  • Data pipelines
  • Feature stores
  • Vector and embedding data systems

Reusable AI Services & Enterprise Abstractions

• Build reusable AI platform services, including:
  • APIs and SDKs for model access
  • Standardized pipelines and workflows
  • Shared components for prompt, model, and agent management
• Reduce duplication and accelerate development across business teams

Performance, Scalability & Cost Optimization

• Engineer platforms to support:
  • Large-scale model training and inference
  • High-throughput, low-latency AI services
• Optimize across:
  • Compute utilization (GPU/accelerators)
  • Cost efficiency
  • Model performance

Developer Experience & Enablement

• Deliver developer-first AI platforms, including:
  • Self-service model development and deployment
  • Tooling for experimentation and evaluation
  • Simplified integration into business applications
• Reduce friction for:
  • Data scientists
  • ML engineers
  • Application developers

Innovation & Continuous Evolution

• Evaluate and incorporate:
  • Emerging AI models and frameworks
  • Advances in GenAI and agentic systems
  • New tooling and infrastructure innovations
• Drive ongoing modernization of AI platforms

Enterprise Technology Collaboration

• Partner with:
  • Global Technology Services (GTS)
  • Cloud and infrastructure engineering teams
  • Cyber security and platform engineering
• Ensure AI platforms meet enterprise standards for:
  • Security
  • Scalability
  • Operational resilience

Qualifications & Experience

• Senior leadership experience managing large-scale (100+) engineering organizations
• Deep expertise in:
  • AI/ML platforms and systems
  • Generative AI and LLM ecosystems
  • Distributed systems and cloud-native architectures
• Proven experience building production-grade AI platforms at enterprise scale
• Strong experience implementing:
  • SRE practices for AI systems
  • Agile and product-based engineering models
• Experience in financial services or similarly complex, regulated environments preferred

Leadership Profile

• Deep AI and platform engineering leader with strong technical credibility
• Combines innovation with disciplined execution
• Brings a strong platform-as-a-product mindset
• Able to operate across cutting-edge AI and enterprise-scale systems
• Collaborative leader across data, architecture, and business teams

Salary Range:

$225,000 - $337,500 Annual

The range quoted above applies to the role in the primary location specified. If the candidate would ultimately work outside of the primary location above, the applicable range could differ.

Employees are eligible to participate in State Street’s comprehensive benefits program, which includes: our retirement savings plan (401K) with company match; insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages; paid-time off including vacation, sick leave, short term disability, and family care responsibilities; access to our Employee Assistance Program; incentive compensation including eligibility for annual performance-based awards (excluding certain sales roles subject to sales incentive plans); and, eligibility for certain tax advantaged savings plans.

For a full overview, visit https://hrportal.ehr.com/statestreet/Home

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.

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