AI Project Manager

In this AI Project Manager role, you drive the end-to-end delivery of AI and technology initiatives to deliver measurable business benefits. You will own project plans, backlogs, and resources while coordinating multidisciplinary teams through discovery, development, testing, release, and handover. You’ll lead stakeholder engagement, communications, training, and change activities to embed AI-enabled ways of working. This opportunity suits a results-driven professional who thrives on cross-functional delivery and wants to shape AI adoption at scale.

• Lead end-to-end delivery of AI and technology projects, including plans, milestones, risks, and status reporting
• Maintain backlogs, user stories, tasks, and acceptance criteria in Azure DevOps or Jira
• Coordinate sprint planning, resource allocation, and capacity across technical and business teams
• Facilitate collaboration across discovery, development, testing, release, and operational handover
• Support AI adoption activities with stakeholder engagement, training coordination, and user feedback collection
• Track delivery and benefits against success measures and escalate issues related to scope, budget, or timelines
• Ensure clear ownership of actions and maintain quality project documentation and governance artefacts
• Contribute to change management to embed AI-enabled processes in daily business activities

• Experienced project manager with a track record in technology or digital transformation projects, ideally including AI or automation
• Familiarity with software delivery lifecycle and Agile ways of working
• Hands-on experience with Azure DevOps, Jira or similar tools for tickets, backlog management, and criteria definition
• Strong organisational skills to manage multiple workstreams and coordinate multidisciplinary teams
• Clear, credible communication influencing both business and technical stakeholders
• Experience in change management, stakeholder engagement, training, and feedback loops
• Ability to track budgets, benefits, and adoption metrics with risk escalation discipline
• Motivation to deepen AI and generative AI expertise and apply it to business problems

• strong communication
• stakeholder engagement
• change management
• Azure DevOps
• Jira
• Agile delivery