Job Openings AI Product Manager

About the job AI Product Manager

Summary of Role

AI Product Manager with experience driving product strategy, discovery, and delivery across AI, data, digital, and technology initiatives. Proven ability to identify business opportunities, define product requirements, prioritise roadmaps, and deliver AI-enabled solutions that create measurable business value. Skilled in translating complex business problems into scalable products, working closely with data scientists, engineers, architects, governance teams, and business stakeholders. Strong understanding of AI, Machine Learning, Generative AI, Responsible AI, data governance, product evaluation, and commercialisation strategies.

Responsibilities

AI Product Strategy & Discovery

  • Identify, assess, and prioritise AI opportunities based on business value, feasibility, risk, cost, and data readiness.
  • Define product vision, business outcomes, value propositions, and success measures.
  • Develop business cases, investment proposals, and prioritisation frameworks.
  • Conduct market research, competitor analysis, and customer discovery activities.

Product Requirements & Design

  • Own and maintain product requirements documentation.
  • Define user journeys, business rules, feature specifications, success criteria, and acceptance metrics.
  • Translate business requirements into clear deliverables for technical teams.
  • Define human oversight, exception handling, escalation paths, and fallback processes.

AI & Data Product Delivery

  • Partner with Data Scientists, AI Engineers, ML Engineers, Architects, and Product Development teams.
  • Support model and technology selection based on business objectives, quality, explainability, cost, security, and scalability.
  • Define data requirements, readiness criteria, governance controls, and integration requirements.
  • Manage product backlogs, sprint priorities, delivery milestones, and release planning.

Product Evaluation & Performance Management

  • Define evaluation frameworks, testing approaches, KPIs, success metrics, and monitoring requirements.
  • Establish benchmarks, acceptance thresholds, and model performance criteria.
  • Monitor product adoption, quality, business outcomes, operational efficiency, and cost performance.
  • Drive continuous improvement initiatives using performance insights and user feedback.

Responsible AI & Governance

  • Ensure compliance with Responsible AI principles, governance frameworks, privacy requirements, and regulatory obligations.
  • Engage Risk, Security, Legal, Compliance, and Governance stakeholders throughout the product lifecycle.
  • Manage approvals, controls, operational ownership, and risk remediation activities.

Commercialisation & Value Realisation

  • Define product positioning, pricing models, and value propositions.
  • Assess product profitability, ROI, cost recovery models, and consumption-based pricing approaches.
  • Support change management, adoption, training, communication, and stakeholder engagement activities.
  • Measure realised business value against approved business cases.

Qualifications

  • Matric and a Bachelor's Degree in Computer Science, Information Systems, Engineering, Data Science, Business Science, or a related discipline.
  • 5+ years of Product Management, Product Ownership, Business Analysis, Product Discovery, or Digital Product Delivery experience.
  • Experience delivering AI, Data, Analytics, Digital Transformation, or Enterprise Technology products.
  • Experience working in Agile environments with product roadmaps, backlogs, user stories, and sprint delivery.
  • Experience building business cases, ROI models, and value-realisation frameworks.
  • Experience managing cross-functional teams and engaging senior stakeholders.

AI & Data Experience

  • Knowledge of Artificial Intelligence, Machine Learning, and Generative AI technologies.
  • Experience with AI pilots, proof of concepts, experimentation, model evaluation, and performance monitoring.
  • Understanding of data governance, data quality, data modelling, metadata, and analytics.
  • Knowledge of Responsible AI, AI governance, ethics, privacy, and compliance requirements.


Technical Skills

Product Management

  • Product Strategy
  • Product Discovery
  • Product Ownership
  • Roadmap Development
  • Backlog Management
  • Agile Delivery
  • User Story Development
  • Acceptance Criteria
  • Prioritisation Frameworks

AI & Data

  • Artificial Intelligence (AI)
  • Machine Learning (ML)
  • Generative AI
  • Prompt Engineering
  • Model Evaluation
  • AI Governance
  • Data Governance
  • Data Quality Management
  • Data Readiness

Analytics & Reporting

  • Power BI
  • Tableau
  • Qlik
  • Azure Monitor
  • Application Insights
  • Business Performance Measurement

Delivery & Collaboration Tools

  • Azure DevOps
  • Jira
  • Confluence
  • Microsoft 365
  • Teams

Preferred Certifications

Product & Agile

  • PSPO (Professional Scrum Product Owner)
  • CSPO (Certified Scrum Product Owner)
  • SAFe Product Owner/Product Manager (POPM)
  • CBAP
  • PMI-PBA

AI & Data

  • Microsoft AI Engineer Associate
  • Microsoft Applied Skills (AI & Copilot)
  • Azure AI Fundamentals (AI-900)
  • AWS AI Practitioner
  • Google AI Certifications
  • OpenAI or Anthropic AI Certifications
  • Data Governance Certifications

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