Delivery Manager

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

Qualifications :

Required Experience and Skills

• Proven leadership delivering software data or AI programmes across multiple parallel streams

• Strong agile delivery capability including backlog ownership prioritisation execution cadence and dependency management

• Experience running production services with operational accountability such as SLOs incident management and release discipline

• Ability to work within architecture security privacy and governance constraints while maintaining delivery speed

• Strong product judgement for platform trade-offs including roadmap decisions usability adoption and service model

• Excellent communication skills including executive reporting risk management and stakeholder alignment

Nice to Have

• Experience delivering GenAI solutions MLOps or AI-enabled automation in enterprise environments

• Familiarity with Microsoft ecosystem including Azure M365 Teams and Copilot and related integration patterns

• Experience implementing AI evaluation safety and compliance gates at scale

Working Style

• Pragmatic and outcome-driven with the ability to balance speed reliability and risk controls

• Comfortable operating in ambiguity creating structure and building repeatable delivery and platform playbooks

• Strong coach and people leader capable of scaling teams and improving delivery maturity

Remote Work :

Yes

Employment Type :

Full-time