← back to jobs
> job detail
F
👽Other

Product Manager, Generative AI & Analytics

Ford Motor · Chennai, Tamil Nadu, India
// classified as
Other (Adjacent or hard to classify.)
posted
1d ago
location
Chennai, Tamil Nadu, India
languages
—
tools
azure
> stack
azure
> description

What Success Looks Like

User Adoption

  • Increase active engagement across business users, analysts, developers, and operational teams.
  • Demonstrate sustained growth in product adoption and usage.

Accuracy and Trust

  • Deliver reliable AI experiences with measurable improvements in response quality, relevance, and user satisfaction.
  • Establish evaluation frameworks that ensure transparency and confidence in AI-generated outputs.

Productivity Impact

  • Improve business, analyst, and developer productivity through AI-powered automation and insights.
  • Reduce manual effort and accelerate access to information and decision support.

Scalability and Enablement

  • Enable onboarding of additional domains, functions, and teams through reusable AI capabilities and improved metadata quality.
  • Increase organizational readiness for enterprise AI adoption.

Product Strategy and Vision

  • Define and execute the product strategy, roadmap, and long-term vision for AI enablement capabilities.
  • Identify opportunities where AI can improve productivity, automation, insight generation, and user experience.
  • Align product priorities with business objectives and enterprise digital transformation strategies.

Product Discovery and User Experience

  • Conduct research with business users, analysts, engineers, developers, and operational stakeholders.
  • Identify user pain points and opportunities through data-driven discovery and experimentation.
  • Translate customer needs into product requirements, user stories, epics, and measurable success criteria.

AI Product Delivery

  • Partner closely with engineering, data science, UX, and platform teams to develop and launch AI-powered products.
  • Guide development of conversational interfaces, AI assistants, natural language analytics, and developer productivity tools.
  • Define experimentation frameworks and evaluation methodologies for AI capabilities and model performance.

Metrics and Business Value

  • Establish KPIs and success measures focused on adoption, engagement, productivity, quality, trust, and operational efficiency.
  • Monitor product outcomes and continuously optimize based on user feedback and behavioural insights.
  • Develop business cases and value realization frameworks for AI investments.

Governance and Responsible AI

  • Champion Responsible AI principles, governance frameworks, and compliance requirements.
  • Promote metadata quality, knowledge management, explainability, and trustworthy AI practices.
  • Partner with security, legal, and governance stakeholders to ensure policy compliance.

Stakeholder Management

  • Build strong partnerships across business functions, technology organizations, and senior leadership.
  • Communicate product vision, strategy, roadmap, risks, and outcomes effectively to executive and technical audiences.
  • Drive organisational adoption and change management activities for AI-powered capabilities.

  • Required

    • Bachelor's degree in Business, Computer Science, Engineering, Information Systems, Data Science, or a related field.
    • 8-10 years of Product Management experience.
    • Demonstrated experience delivering AI, analytics, data, or developer-focused products.
    • Strong understanding of Generative AI, Large Language Models (LLMs), Natural Language Processing (NLP), and conversational interfaces.
    • Experience defining product strategy, roadmaps, and outcome-based success metrics.
    • Strong stakeholder management and cross-functional leadership skills.
    • Experience working with engineering, machine learning, user experience, and business teams.
    • Excellent written, verbal, presentation, and storytelling skills.

    Preferred

    • Experience launching enterprise AI or Generative AI products at scale.
    • Experience with cloud platforms such as Azure, Google Cloud Platform (GCP), or AWS.
    • Familiarity with enterprise data platforms, analytics ecosystems, and knowledge management solutions.
    • Experience defining evaluation frameworks for AI quality, trust, and model performance.
    • Prior experience in developer productivity, internal platforms, or enterprise tooling products.
    • MBA or advanced degree in a related discipline.

      #LI-SKV
Apply at Ford Motor →