Team: UKI Platform & Enablement – AI Platform
Role Overview
This is a critical leadership role within the Flutter UK & Ireland AI Platform initiative.
The AI Engineering Team Manager will be responsible for building and leading a high-performing engineering squad across multiple locations, focused on delivering core components of a multi-tenant, enterprise-grade AI platform. This platform will underpin the next generation of AI capabilities across the business — from internal assistants (e.g. Flint) through to advanced agentic systems and domain-specific AI services.
You will combine hands-on technical leadership with people leadership, ensuring high-quality engineering delivery while shaping best practices for building scalable, secure, and production-ready AI systems on AWS.
Key Responsibilities
Engineering Leadership
Role Overview
This is a critical leadership role within the Flutter UK & Ireland AI Platform initiative.
The AI Engineering Team Manager will be responsible for building and leading a high-performing engineering squad across multiple locations, focused on delivering core components of a multi-tenant, enterprise-grade AI platform. This platform will underpin the next generation of AI capabilities across the business — from internal assistants (e.g. Flint) through to advanced agentic systems and domain-specific AI services.
You will combine hands-on technical leadership with people leadership, ensuring high-quality engineering delivery while shaping best practices for building scalable, secure, and production-ready AI systems on AWS.
Key Responsibilities
Engineering Leadership
- Build, lead, and develop a cross-functional engineering team (backend / full stack)
- Set engineering standards, patterns, and ways of working aligned to platform-first principles
- Drive a culture of ownership, quality, and continuous improvement
Platform Delivery
- Lead the design and delivery of core AI platform services (APIs, orchestration layers, integration services)
- Contribute to the development of a multi-tenant AI control plane with built-in governance, security, and observability
- Ensure solutions are scalable, reusable, and aligned to enterprise architecture standards
Technical Direction
- Provide hands-on guidance across system design, architecture, and implementation
- Partner with Architecture, Security, and Platform teams to ensure alignment with AWS best practices (incl. Bedrock and cloud-native services)
- Support design reviews and contribute to Technical Design Authority (TDA) processes
AI & Emerging Technology
- Enable the team to build AI-powered services, including LLM integrations, agent frameworks, and retrieval-based systems
- Ensure responsible AI practices are embedded (guardrails, auditability, data controls)
Delivery & Collaboration
- Work closely with Product, Business Analysis, and Engagement teams to translate use cases into deliverable outcomes
- Support iterative MVP delivery, balancing speed with long-term platform integrity
- Collaborate across UK&I and International teams to drive consistency and reuse
Skills & Experience
Essential
Essential
- Strong experience as a senior or lead engineer in backend or full stack development
- Proven experience leading engineering teams and delivering complex distributed systems
- Experience building cloud-native applications on AWS (e.g. Lambda, API Gateway, ECS, DynamoDB, etc.)
- Strong understanding of system design, APIs, and microservices architecture
- Experience working in agile environments with modern engineering practices
Desirable
- Experience working with AI/ML systems or integrating with LLMs (e.g. Amazon Bedrock or similar)
- Knowledge of multi-tenant architectures and platform engineering concepts
- Experience with observability, security, and governance in enterprise systems
- Familiarity with event-driven architectures and data pipelines
Why This Role
- Opportunity to shape and build a greenfield AI platform at enterprise scale
- Direct impact on how AI is delivered across Flutter UK & Ireland
- Work at the intersection of platform engineering, AI, and product innovation
- Build and lead a team in a high-visibility, strategically critical programme
Success Measures
- Successful build and growth of a high-performing engineering team
- Delivery of scalable, reusable AI platform components
- Adoption of platform services across multiple teams and use cases
- High standards of engineering quality, security, and reliability
