Senior Consultant - Business Consulting at Infosys · Location…

AI Product Owner

Enterprise AI practice

Do you want to boost your career and collaborate with expert, talented colleagues to solve and deliver against our clients' most important challenges? We are growing and are looking for people to join our team. You'll be part of an entrepreneurial, high-growth environment of over 320,000 employees. Our dynamic organization allows you to work across functional business pillars, contributing your ideas, experiences, diverse thinking, and a strong mindset. Are you ready?

The Role

We are looking for client-facing AI Product Owners to join our growing Enterprise AI practice. As an AI Product Owner you will sit at the intersection of business strategy, user needs, data and emerging AI capabilities — defining where AI should be applied, why it matters and how the value is realised for our clients. You will shape AI use cases, frame the business cases that justify investment, prioritise roadmaps, and be a trusted voice on Responsible AI throughout the product lifecycle.

You will work in cross-functional teams alongside data scientists, ML and GenAI engineers, designers, and our clients’ business owners — typically embedded inside client delivery teams connecting business intent and AI engineering.

This role is offered across a broad seniority band, from AI Product Owners with around 2–3 years of product ownership experience and early AI exposure, through to Lead AI Product Owners with 10+ years of product experience leading complex multi-product portfolios.

Key Responsibilities

• Shape AI use cases — identify where machine learning, generative AI and agentic AI can solve real business problems, and equally where they cannot
• Frame business cases and value hypotheses for AI products, including success metrics for probabilistic systems and the realistic costs, risks and dependencies
• Own and prioritise the AI product backlog, translating ambiguous opportunities into well-scoped, testable increments that data science and engineering teams can deliver
• Define product vision and roadmaps for AI-enabled products, balancing experimentation with production-grade delivery
• Translate business problems into AI problems — specify data requirements, evaluation criteria, acceptance criteria and guardrails for ML and GenAI features
• Advise on Responsible AI in everyday product decisions — fairness, transparency, accountability, human oversight and proportionate risk management
• Guide AI products across the full lifecycle: ideation, data readiness, prototyping, evaluation, deployment, monitoring and continuous improvement
• Engage business stakeholders, subject matter experts and end users to validate problems, test prototypes and drive adoption
• Collaborate with distributed delivery teams, including offshore, to ensure quality and pace
• Contribute to Infosys Consulting’s thought leadership, accelerators and reusable assets for AI Product Management