Required Skills: Product Management, product ownership, AI/ML products, GenAI, AI platform, AI/ML lifecycle management, AI evaluations, data science, Business Analysis

Job Description

• • Define and own the AI platform product roadmap, vision, and backlog.
  • Drive evaluation-driven development to measure AI/ML model quality, performance, reliability, and business outcomes.
  • Establish and automate AI governance, controls, and approval workflows.
  • Define requirements for AI model lifecycle management, from development and evaluation through deployment, monitoring, and retirement.
  • Drive implementation of production monitoring and observability for AI/ML applications.
  • Develop product capabilities that support risk management, security, compliance, and responsible AI practices.
  • Partner with engineering and data science teams to prioritize features and translate business requirements into
  • actionable epics, user stories, and acceptance criteria.
  • Define and track adoption, usage, quality, and business-impact metrics.
  • Drive enterprise adoption by identifying user needs, removing adoption barriers, and improving platform usability.
  • Work with executive stakeholders to communicate product strategy, roadmap progress, risks, adoption trends, and business outcomes.
  • Collaborate with security, legal, risk, and compliance teams to ensure AI products meet enterprise standards and regulatory requirements.
  • Establish product governance processes, operating models, and documentation standards.
  • Conduct  stakeholder reviews and continuously prioritize the backlog based on business value, risk, and technical feasibility. 

     

    Required Skills & Experience:

     

     

    • 8+ years of experience in Product Management / Product Ownership.
    • Strong experience owning enterprise platform products and product roadmaps.
    • Hands-on understanding of AI/ML products, GenAI, or AI platforms.
    • Experience with AI evaluations, model performance measurement, testing, and quality frameworks.
    • Strong understanding of AI governance, controls, risk management, and responsible AI.
    • Experience with AI/ML lifecycle management and production deployment.
    • Strong understanding of observability and production monitoring for AI/ML systems.
    • Experience defining and tracking product adoption and business metrics.
    • Strong Agile experience with backlog management, user stories, epics, prioritization, and sprint planning.
    • Excellent stakeholder management skills across engineering, business, security, risk, and compliance teams.
    • Experience presenting roadmaps, KPIs, risks, and product performance to senior/executive leadership.