Agile Product Manager

About the role

We are seeking an experienced Agile Product Manager to lead AI engagement initiatives. You will translate business goals into a prioritized, testable backlog, define success criteria for non‑deterministic systems, and drive adoption once the solution ships.

Key responsibilities

• Own the product backlog for AI engagements, shaping outcome‑focused epics and prioritising by value, feasibility and risk.
• Translate business outcomes into AI use cases with explicit success criteria and acceptance thresholds.
• Run discovery workshops with client stakeholders to differentiate real problems from AI‑driven solutions.
• Define “good enough” for probabilistic systems, establishing AI Assurance jointly with the client.
• Manage the release plan across PoC, pilot and scale phases, including human‑in‑the‑loop and fallback behaviours.
• Prioritise data readiness and integration work alongside model development.
• Facilitate sprint ceremonies, keep the delivery pod unblocked and aligned to a single set of priorities.
• Handle scope, timeline and client expectations when model performance is uncertain.
• Lead adoption and change management activities – training, rollout communications and usage measurement.
• Track value realisation post‑launch and feed insights back into the roadmap.
• Secure responsible‑AI and governance sign‑off within the delivery flow.

Required profile

• 10+ years of product management or product ownership experience, including at least 3 years on AI/ML or data‑intensive products.
• Deep fluency in agile delivery (Scrum, Kanban, SAFe) and ability to own a backlog under tight timelines.
• Strong understanding of the AI delivery lifecycle – data readiness, model evaluation, deployment, monitoring and retraining.
• Ability to assess feasibility, cost and latency claims without designing the solution.
• Experience writing acceptance criteria for probabilistic outputs, including thresholds, guardrails and escalation paths.
• Proven track record of running change‑management and adoption programmes for systems that alter user workflows.

Required skills

• Scrum
• Kanban
• SAFe
• AI/ML product knowledge
• AI evaluation
• Observability
• Responsible AI
• Data integration