AI Product Manager

Product Manager (AI & Process Automation) Location: Remote Open Position : 1 About the Engagement You will be the sole Product Manager embedded in a cross-functional engineering team building a cloud-agnostic, multi-tenant platform for deploying, certifying, and distributing AI agents at enterprise scale. This is a greenfield platform engineering programme running across three phases over approximately 12 months, delivered for a government-aligned client. What You Will Own Backlog & Prioritisation Define and maintain the product backlog across all three phases. Translate SOW deliverables into sprint-ready user stories with clear acceptance criteria. Make prioritisation calls when scope, time, and quality are in tension. Persona & Requirements Management The platform serves four distinct personas — Agent Developer, Platform Engineer, Security/Compliance Officer, and Product Manager (internal). You own the requirements and success criteria for each persona across the portal, evaluation pipeline, certification workflow, and marketplace catalog. Stakeholder Management Primary interface between the Turing delivery team and client product and operations stakeholders. Run structured discovery sessions, demo sprint outcomes, collect feedback, and convert it into actionable backlog items. Phase Gate Ownership Define and enforce exit criteria for each phase. Ensure Phase 1 single-tenant provisioning, Phase 2 multi-tenancy and governance, and Phase 3 certification and marketplace launch are delivered against agreed scope — not just technically complete but operationally ready. Compliance Awareness Understand the product implications of KSA's PDPL and NDMO framework. Ensure user-facing features — data handling flows, consent mechanisms, audit trails — are built with regulatory requirements reflected in acceptance criteria, not retrofitted. Must-Have 7+ years in product management, with at least 2 years on platform or infrastructure products Experience owning backlogs for technical platforms — APIs, developer tooling, or data platforms Comfortable writing detailed user stories and acceptance criteria for engineering audiences Strong stakeholder management across engineering, client, and executive layers Experience running agile delivery (Scrum or Kanban) with distributed teams Familiarity with AI/ML concepts — enough to hold substantive conversations with GenAI and ML engineers Hands-on with Jira, Confluence, or equivalent backlog and documentation tooling Good experience in marketplace(AI/Non-AI)/Platform(AI/Non-AI) Nice-to-Have Prior experience on agent platforms, LLM tooling, or AI marketplace products Exposure to KSA or broader GCC market engagements Understanding of data privacy regulations (PDPL, GDPR, or equivalent) Experience working on multi-tenant SaaS or PaaS platforms Familiarity with SOW-driven delivery models and commercial milestone structures