Global Head of AI Platform Engineering, SVP
Role details
Job location
Tech stack
Job description
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., + 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, + 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, * 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, * 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
Requirements
Do you have experience in Technical architecture?, * 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
Benefits & conditions
Pulled from the full job description
- Health insurance
- 401(k) matching
- Paid time off
- Vision insurance
- Dental insurance
- Employee assistance program
- Disability insurance, $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., 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.