Senior AI Product Manager – Product & Experience

Overview

Senior AI Product Manager at Capco leads the shaping and scaling of AI-enabled products and experiences. You translate AI capabilities into real-world value, working with clients and cross-functional teams to deliver commercially impactful, user-centric, production-ready solutions within regulated environments. You leverage AI tooling to accelerate discovery, decision-making, and delivery while maintaining governance and risk awareness. This role blends strategy, delivery, and leadership to drive measurable business outcomes in financial services and energy.

Pay / Benefits

• Discretionary bonus
• Competitive pension
• Health insurance
• Life insurance
• Critical illness cover
• Mental health support (CareFirst, Unmind)

Responsibilities

• Lead AI-enabled product engagements across clients and Capco teams, integrating AI into strategy and delivery
• Define AI-native product strategies, including value propositions, roadmaps, and commercialization models
• Own products end-to-end from discovery to delivery and iteration with rapid experimentation
• Identify and prioritize AI/GenAI/ML use cases and translate them into scalable features with measurable outcomes
• Collaborate with data science and engineering to productionize ML models while balancing performance, risk, and cost
• Embed responsible AI through governance, explainability, and regulatory considerations in product design
• Mentor multidisciplinary teams and foster a culture of experimentation and AI/data fluency

Key requirements

• Experience delivering digital products across B2B/B2C/B2B2C in financial services or energy
• Proven track record building or scaling AI/data/platform-enabled products, incl. GenAI/LLM
• Ability to define AI-driven use cases with measurable impact (revenue, efficiency, engagement)
• Strong leadership with senior stakeholders and cross-functional teams
• Experience with data-led or platform products
• Understanding of AI, GenAI, or agentic AI concepts and product applications

• leadership of multidisciplinary teams
• stakeholder management
• continuous learning and experimentation
• AI/GenAI/LLM concepts
• AI governance and regulatory considerations
• product management for AI-enabled platforms

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