AI Project Manager
AI Project Manager - AI Rollout (Claude)
Role Overview
We are seeking an experienced AI Project Manager to lead the end-to-end rollout of Claude AI solutions across a major client organisation. This role will act as the central delivery lead across strategy, implementation, governance, stakeholder engagement, vendor management, and adoption.
The successful candidate will oversee the full lifecycle of the AI deployment, from discovery and use-case definition through implementation, training, rollout, optimisation, and operational governance. The role requires strong programme management capabilities combined with excellent communication and writing skills, as the individual will be responsible for producing executive-level documentation, rollout communications, policies, training materials, and client-facing deliverables.
This is a highly cross-functional role working across client stakeholders, internal delivery teams, AI vendors, security, legal, operations, and change management functions.
Key Responsibilities
AI Rollout & Programme Delivery
- Lead the end-to-end deployment of Claude AI across the client organisation
- Define and manage project scope, timelines, deliverables, budgets, and risks
- Coordinate cross-functional teams including technical, operational, legal, compliance, and business stakeholders
- Develop phased rollout strategies and adoption plans
- Manage pilot programmes, feedback loops, and scaling initiatives
- Track delivery progress and provide regular reporting to leadership teams
Vendor & Partner Management
- Act as the primary point of contact for AI vendors and implementation partners
- Manage vendor relationships, contracts, deliverables, SLAs, and escalation processes
- Coordinate with platform providers and third-party integrators to ensure successful deployment and support
- Evaluate vendor performance and identify optimisation opportunities
Stakeholder Engagement & Communication
- Build strong relationships with executive sponsors and business stakeholders
- Facilitate workshops, steering committees, and governance meetings
- Translate technical AI concepts into clear business language
- Drive alignment between business goals and AI implementation strategies
Writing & Documentation
- Produce high-quality project documentation, business cases, rollout plans, governance frameworks, and executive presentations
- Develop AI usage policies, operating procedures, and risk management documentation
- Create user guides, training content, FAQs, communications, and adoption materials
- Draft client-ready reports and implementation updates
Governance, Risk & Compliance
- Ensure AI deployment aligns with organisational governance, security, and compliance requirements
- Support responsible AI practices, data privacy standards, and risk mitigation activities
- Coordinate approvals across legal, procurement, cybersecurity, and compliance functions
Adoption & Change Management
- Drive user adoption initiatives and change management activities
- Support training programmes and enablement sessions for end users and leadership teams
- Gather user feedback and identify continuous improvement opportunities
- Measure adoption, engagement, and operational impact
Required Skills & Experience
- Proven experience managing enterprise technology or AI transformation programmes
- Experience delivering end-to-end software or SaaS implementations
- Strong vendor and stakeholder management experience
- Excellent written communication and documentation skills
- Ability to manage multiple workstreams in complex client environments
- Strong organisational and problem-solving skills
- Experience working with executive stakeholders and cross-functional teams
- Familiarity with AI tools, large language models, or generative AI platforms such as Claude, ChatGPT, or Microsoft Copilot
Preferred Experience
- Experience with enterprise AI governance or responsible AI frameworks
- Background in consulting, digital transformation, or technology delivery
- Experience within regulated industries or large enterprise environments
- Understanding of change management and user adoption strategies
- Knowledge of Agile, Scrum, or hybrid project delivery methodologies
Success Measures
- Successful rollout and adoption of Claude AI across the client organisation
- Delivery against project timelines, budgets, and quality expectations
- Positive stakeholder engagement and user adoption metrics
- Effective governance and operational management of AI capabilities
- High-quality written deliverables and executive communications