AI Product Owner – Consultant

Role Overview

• 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

Requirements

• 2+ years of hands-on Product Ownership experience (rising to 10+ at the more senior levels)
• 1+ years applying product ownership specifically to AI, ML or data products
• Strong understanding of how AI, ML, GenAI and agentic AI differ from traditional software — particularly around probabilistic behaviour, data dependency, evaluation and monitoring
• Demonstrable ability to translate business problems into well-framed AI problems, and back into measurable business outcomes
• Experience working in Agile / Scrum delivery, owning a backlog and partnering with technical teams
• Strong stakeholder management — comfortable engaging with both technical contributors and business leaders
• Depth in at least one industry or one functional domain, with the curiosity and adaptability to operate credibly in new contexts
• Working knowledge of Responsible AI principles — fairness, transparency, accountability, human oversight
• Familiarity with current thinking in AI Product Management
• Excellent written and verbal communication in English
• Bachelor’s degree; quantitative or technical disciplines are an advantage
• Willingness to travel — up to around 60% depending on project (UK and international)
• A second major European language is an advantage
• Functional depth in customer service, marketing, HR, procurement, finance, sales or IT operations
• Awareness of specific Responsible AI frameworks — for example the EU AI Act, NIST AI RMF, or ISO/IEC 42001
• Hands-on familiarity with model evaluation, prompt evaluation, RAG architectures, MLOps concepts and observability for AI systems (essential at Senior and Lead levels)
• Knowledge of partner platforms — agentic workflow tooling, hyperscaler AI platforms (AWS, Azure, Google Cloud), modern data platforms
• Consulting or comparable client-facing delivery experience
• At more senior levels: experience leading distributed and offshore teams, shaping deal pursuits and developing junior talent
• AI Product Academy certification
• Certified Scrum Product Owner (CSPO) or SAFe Product Owner / Product Manager (POPM)
• Hyperscaler AI/ML certifications — AWS, Microsoft Azure or Google Cloud
• Responsible AI / AI governance credentials (e.g. IAPP AIGP)

Tech Stack

• AWS
• Azure
• Cloud

Benefits

• About Enterprise AI
• Health insurance
• 401(k) matching
• Flexible working hours
• Paid time off
• Professional development opportunities