Broadridge
Product Manager
Skills
3 months ago
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Important information
Contract type:
Permanent
Location:
Bengaluru, Karnataka, India
Work mode:
Hybrid
Published on:
7 August 2026
What they need
Senior Product Manager AI Transformation
We are looking for a Senior Product Manager AI Transformation to drive enterprise AI initiatives from business problem discovery to production-ready solutions. This role will work closely with business stakeholders, BUs, engineering, data, AI architecture, and governance teams to identify high-impact AI opportunities, define requirements, shape product roadmaps, and deliver measurable business outcomes.
Key Responsibilities
- Partner with business stakeholders and cross-functional BUs to identify, prioritize, and scope AI transformation opportunities.
- Translate business problems into clear product requirements, user stories, success metrics, and delivery roadmaps.
- Work with AI architects, ML engineers, data teams, and platform teams to build scalable AI/ML, GenAI, LLM, RAG, and agentic AI solutions.
- Own end-to-end product delivery from discovery, solution design, MVP definition, rollout, adoption, and value tracking.
- Ensure AI solutions are aligned with enterprise governance, security, compliance, cost, and responsible AI standards.
- Drive stakeholder communication, change management, user adoption, and executive reporting.
Required Experience
- More than 8 years of experience in Product Management, AI/ML product delivery, digital transformation, or enterprise technology programs.
- Proven experience building or delivering AI solutions in production, preferably involving GenAI, LLMs, RAG, automation, predictive analytics, or agentic workflows.
- Strong experience working with senior business stakeholders to gather requirements and convert them into actionable AI product roadmaps.
- Experience collaborating with engineering, data science, architecture, cloud, security, and governance teams.
Key Skills
- AI/ML and GenAI product management
- Business requirements gathering and stakeholder management
- Product roadmap, prioritization, and delivery ownership
- Understanding of LLMs, RAG, agents, data pipelines, APIs, and enterprise AI platforms
- Strong communication, problem-solving, and executive presentation skills
- Outcome-driven mindset with focus on adoption, ROI, scalability, and responsible AI governance
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