Job Title: AI Product / Program Management Manager
Experience: 10+ Years
Location: Bengaluru

We are seeking an experienced AI Product / Program Management Manager to lead the strategy, planning, delivery, and governance of enterprise AI initiatives. The ideal candidate will have a strong background in product management, program delivery, stakeholder management, and AI/GenAI technologies. This role will be responsible for driving AI product roadmaps, managing cross-functional teams, aligning business objectives with AI solutions, and ensuring successful execution from ideation to production.

Key Responsibilities

Product Strategy & Roadmap

• Define and drive the vision, strategy, and roadmap for AI and Generative AI products.
• Identify business opportunities where AI can create measurable value and competitive advantage.
• Work closely with business leaders, clients, and technology teams to prioritize features and use cases.
• Develop product requirements, user stories, success metrics, and business cases.

Program Management & Delivery

• Lead end-to-end delivery of AI initiatives across multiple teams and stakeholders.
• Manage program planning, budgeting, resource allocation, timelines, risks, and dependencies.
• Establish governance frameworks and ensure alignment with organizational objectives.
• Track project progress and provide regular executive-level status updates.

AI & Technology Leadership

• Collaborate with Data Scientists, AI Engineers, Architects, and Business Analysts to design AI-driven solutions.
• Drive adoption of Generative AI, Machine Learning, NLP, Computer Vision, and other emerging AI technologies.
• Evaluate AI platforms, tools, and vendors to support organizational goals.
• Ensure AI products are scalable, secure, and compliant with regulatory requirements.

Stakeholder Management

• Act as the primary interface between business stakeholders, clients, and technical teams.
• Facilitate workshops, requirement-gathering sessions, and executive reviews.
• Communicate program status, risks, and business outcomes to senior leadership.

Governance & Risk Management

• Implement AI governance frameworks covering ethics, compliance, privacy, and security.
• Monitor risks, issues, and mitigation plans across AI programs.
• Ensure adherence to enterprise architecture, data governance, and regulatory standards.

Performance & Value Realization

• Define KPIs and success metrics for AI products and programs.
• Measure business impact, ROI, adoption, and operational efficiency improvements.
• Drive continuous improvement and innovation through data-driven decision making.

Required Qualifications

• Bachelor's or Master's degree in Engineering, Computer Science, Information Technology, Business Management, or related field.
• 10+ years of experience in Product Management, Program Management, Digital Transformation, or Technology Delivery.
• 3+ years of experience leading AI/ML or Generative AI initiatives.
• Strong understanding of AI/ML lifecycle, GenAI applications, LLMs, prompt engineering, and AI governance.
• Proven experience managing large-scale cross-functional programs and stakeholder engagement.
• Strong knowledge of Agile, Scrum, SAFe, and product development methodologies.
• Excellent communication, presentation, negotiation, and leadership skills.

Preferred Qualifications

• MBA or equivalent business qualification.
• Certifications such as PMP, PgMP, SAFe, PMI-ACP, CSPO, or AI-related certifications.
• Experience with Azure AI, Azure OpenAI, AWS AI/ML, Google Vertex AI, Databricks, or similar platforms.
• Experience working in BFSI, Healthcare, Retail, Technology, or Consulting domains.

Key Skills

• AI Product Management
• Program & Portfolio Management
• Generative AI & LLMs
• Machine Learning & Data Analytics
• Product Roadmap & Strategy
• Stakeholder & Client Management
• Digital Transformation
• Agile / Scrum / SAFe
• Risk & Governance Management
• Business Case Development
• Vendor Management
• Executive Communication

Success Metrics

• Successful delivery of AI programs within scope, budget, and timelines.
• Adoption and business impact of AI solutions.
• Improved operational efficiency and customer experience.
• Effective AI governance and compliance adherence.
• Stakeholder satisfaction and measurable ROI realization.