Role Purpose
Own end-to-end delivery of the internal AI portfolio and the OneAI platform as the single front door for safe AI across the business. Accountable for prioritisation and predictable execution across platform capabilities and AI solutions, ensuring quality, operational readiness, measurable value, and adoption in partnership with Enablement and Governance.
Key Responsibilities
1. Portfolio Ownership and Prioritisation
Own and maintain two connected backlogs:
OneAI platform and OneAI Labs, including publishing workflows, templates, governance enablement, telemetry, and UX
AI solutions delivery, including business use cases, automation, and integrations
Drive prioritisation trade-offs between platform roadmap and solution delivery, escalating and aligning through the AI Council when required
Maintain a single, transparent portfolio roadmap with clear milestones, dependencies, and outcomes
2. Delivery Leadership and Execution
Lead delivery across multiple pods and streams, ensuring clear scope, timelines, and value-focused increments
Establish and run delivery operating rhythms including planning, backlog refinement, sprint execution, demos, retrospectives, and release cadence
Manage dependencies across platform, infrastructure, security, data, and enablement workstreams
Ensure each solution is packaged for scale, with reusability via OneAI templates, patterns, and documentation
3. Platform and Operations Leadership
Own OneAI product outcomes including usability, adoption, publishing throughput, and effectiveness as the single front door
Ensure platform engineering follows enterprise standards including architecture, CI/CD, observability, and identity and permissions
Run OneAI as a service, including support model, incident processes, release communications, and platform health reporting
Ensure solutions and agents are publishable and discoverable through OneAI and Labs with appropriate guardrails
4. Quality, Safety, and Release Readiness
Ensure initiatives meet release criteria including testing, evaluation, documentation, monitoring, runbooks, privacy and security controls, and rollout plans
Partner with Responsible AI and Quality teams to embed quality gates, evaluations, regression testing, and safety reviews into the lifecycle
Drive operational learnings back into delivery and platform practices through post-mortems, prevention backlog, and reliability improvements
5. Team and Capability Leadership
Build, lead, and coach cross-functional teams including AI engineers, data scientists, solution architects, automation specialists, and platform engineers
Line manage delivery and platform roles including hiring, performance management, and development
Define clear ownership boundaries and handoffs across pods, platform, and federated partners
6. Stakeholder Management and Value Realisation
Act as the primary delivery and platform point of contact for in-flight work with business and IT stakeholders
Translate objectives into deliverable increments with success metrics and measurable outcomes
Track value and adoption outcomes in partnership with Enablement, including training, communications, change management, and champion activation
Success Measures (KPIs)
Delivery Performance
Delivery predictability including on-time milestones and sprint goal achievement
Reduced unplanned work
Time to value from intake to first usable release and production
Quality and Operational Readiness
Defect leakage, rollback frequency, evaluation pass rates, incident rate
Monitoring coverage, runbook completeness, supportability, and handover quality
OneAI Platform Outcomes
Adoption metrics such as monthly active users and repeat usage
Publishing throughput including time to publish and number of reusable templates, apps, and agents
Platform health including availability, performance, incident trends, and cost signals
Stakeholder Outcomes
Stakeholder satisfaction across business and IT
Measurable value, savings, and reuse rates