We are looking for a dedicated Project Manager to drive an AI workforce transformation programme in a time-bound manner. The programme introduces AI tools and workflow transformations across teams in the software development lifecycle, using a phased, evidence-gated methodology: mobilise, discovery, baseline, solution design, implementation, and measurement — with repeating design–implement–measure cycles per intervention.
This is a governance-heavy, metrics-driven delivery role. You will convert the methodology into a dated, committed programme schedule and hold owners to it; run the weekly and steering cadence; enforce exit-gate discipline (no phase closes without signed-off deliverables, no intervention starts without a frozen, evidence-backed baseline); and give leadership a single, reliable window into progress, risks, and decisions needed. You will work hand-in-hand with the architecture and engineering teams, team leads, tool admins, security/compliance, and finance.
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Build and own the programme schedule: phase-wise, per-team and per-intervention milestones, starting from preliminary discovery data.
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Produce the indicative programme timeline within the first 30 days and keep it continuously current.
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Surface variances early — no silent slippage; escalate ahead of time with options.
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Run the operating cadence: weekly written status to sponsors, steering committee sessions, phase-exit playbacks with team leads.
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Enforce exit-gate discipline: phases close only on filled, reviewed, signed-off programme templates; interventions start only against a frozen baseline.
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Bring scale / iterate / retire decisions to steering on schedule for every intervention.
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Track and clear cross-team dependencies and blockers — team leads, tool admins, security/compliance, finance.
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Maintain the risk and dependency register with weekly refresh.
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Manage the intervention pipeline: prioritised backlog, pilot schedules, rollout waves.
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Coordinate enablement logistics during pilots and rollouts: training sessions, champions, office hours.
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Maintain the single source of truth: versioned template repository, immutable baseline snapshots, decision log.
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Report programme economics with the AI & Architecture team: tool spend, licence utilisation, measured return per intervention.
Domain
Skills & Experience
Must / Preferred
Programme Management
8+ years managing software delivery programmes; multi-team initiatives with formal governance, gates and steering committees
Must
Metrics-Driven Delivery
Comfort with DORA/flow metrics (lead time, cycle time, deployment frequency, MTTR); evidence-gated reporting; baseline vs target tracking
Must
Change & Adoption
Running change/adoption programmes — training plans, champions networks, usage instrumentation and tracking
Must
Stakeholder Management
Client leadership and delivery teams; crisp written reporting; steering-level communication
Must
Delivery Toolchains
Jira/ADO, Git platforms, CI/CD — sufficient fluency to interrogate extracted delivery data
Must
Risk & Dependency Mgmt
Cross-team dependency tracking, risk registers, escalation management
Must
AI-Assisted Engineering
Exposure to AI coding assistants, test generation, CI/CD analytics and their rollout dynamics
Preferred
Distributed Delivery
Experience operating in or with offshore / captive-centre delivery models
Preferred
Agile at Scale
Scrum/SAFe / LeSS / multi-squad agile coordination
Preferred
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Education: Bachelor's degree in Engineering, Computer Science, or a related field (or equivalent); MBA a plus.
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Experience: 8+ years in software delivery / programme management, with at least 3 years running multi-team programmes.
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Track Record: Demonstrated track record of time-bound delivery against formal governance — verifiable through references.
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PMP / PRINCE2 Practitioner
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PMI-ACP, SAFe Program Consultant, or equivalent agile-at-scale certification
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Evidence-First Mindset: Insists on data over anecdote, and comfortable telling leadership what the numbers actually say.
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Firm on Process, Collaborative in Style: Can enforce gates without alienating delivery teams.
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Calm, Structured Operator: Manages concurrent workstreams with strong prioritisation under pressure.
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Excellent Written Communication: Weekly status and steering packs are core deliverables of this role.
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Change-Management Sensitivity: Teams must experience the programme as enablement, not surveillance.
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Ownership of a high-visibility, leadership-sponsored transformation programme from its foundation.
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Direct exposure to AI-in-SDLC adoption at enterprise scale — one of the most in-demand delivery specialisations.
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Work alongside a dedicated AI and architecture practice with a defined, evidence-gated methodology.
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Competitive compensation with a structured performance review process.
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Professional development support — certifications, conferences, and emerging tooling.
