AI Product Manager

You will own the end-to-end lifecycle of AI-powered products from market research and product vision through roadmap planning, development, launch, and iteration. You’ll sit at the intersection of AI engineering, data science, design, and business strategy, translating complex technologies into valuable, user-centric solutions that deliver measurable results.

Key Responsibilities

Product Strategy & Roadmapping
Define the vision and roadmap for AI-driven initiatives. Conduct market analysis to identify AI opportunities and align features with business/market needs. Cross‑Functional Collaboration
Work closely with engineering, ML/data science, UX design, marketing, sales, and stakeholders to shape product requirements from ideation to release. Backlog & Execution Management
Convert business objectives into actionable product backlog items. Prioritise based on impact, feasibility, and user value. Oversee agile delivery through sprints, MVPs, and beta launches. Market & User Research
Conduct ongoing market and competitive analysis, customer interviews, and user testing. Use insights to refine product direction. Performance Monitoring & Analytics
Define and track KPIs (e.g., adoption, retention, accuracy). Use data-driven insights to iterate and optimize AI functionality. Ethics & Risk Management
Ensure compliance with responsible AI practices mitigate bias, privacy, fairness, and regulatory concerns. Implement safeguards in model development and deployment. Go-to-Market & Stakeholder Enablement
Support launch planning, marketing strategy, sales collaterals, training, and evangelism. Keep stakeholders (execs, partners) informed of progress and impact.

Required Skills & Experience

Technical Knowledge

Appreciation of AI/ML fundamentals: algorithms, model training & evaluation, NLP/CV, model validation. Familiarity with tooling and platforms (Python, cloud AI services, data pipelines, MLOps) .

Product & Domain Expertise

5-7+ years in Product Management, ideally with AI/ML or data-driven products. Demonstrated success launching AI solutions . Experience in agile methodologies (Scrum/Kanban) and backlog management .

Analytical & Strategic Abilities

Ability to plan and manage the analysis of data, insights and ML development, and drive decisions from metrics and user feedback . Strong business acumen to frame AI as strategic tools that solve real problems (not AI for AI’s sake)

Soft Skills

Excellent communication: able to bridge technical and non-technical stakeholders, and write clear PRDs/user stories Empathy and leadership: manage diverse, cross-functional teams with clarity and alignment . Adaptability and creativity to navigate fast-moving AI landscape