AI Product Owner - Consultant

Our Enterprise AI practice supports the largest global organisations to find and deliver business value from data & AI. We work within the broad Infosys ecosystem partnering with deep industry and domain experts to find transformational value and then enable clients to bridge from strategy through to implementation collaborating with our global delivery organisation. Examples of our work include developing AI transformation roadmaps, setting up AI Centres of Excellence, data strategy and readiness assessments, automating complex workflows with multi-agent systems and intelligent document processing with generative AI. We always bring a human-centred and value-led approach to technology transformation.

Infosys Consulting is a globally renowned management consulting firm on the front-line of industry disruption and at the cutting edge of technology. We work with market leading brands across sectors. Our culture is inclusive and entrepreneurial. Being a mid-size consultancy within the scale of Infosys gives us the global reach to partner with our clients throughout their transformation journey.

• 2+ years of hands-on Product Ownership experience (up to 10+ years at senior levels)
• 1+ years applying product ownership specifically to AI, ML, or data products
• Strong understanding of AI, ML, GenAI, and agentic AI differences from traditional software, especially probabilistic behavior, data dependency, evaluation, and monitoring
• Ability to translate business problems into well-framed AI problems and measurable business outcomes
• Experience working in Agile/Scrum delivery, owning a backlog, and partnering with technical teams
• Strong stakeholder management skills engaging technical contributors and business leaders
• Depth in at least one industry or functional domain with adaptability to new contexts
• Working knowledge of Responsible AI principles: fairness, transparency, accountability, human oversight
• Familiarity with current AI Product Management thinking
• 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

Preferred Skills:

• A second major European language
• Functional depth in customer service, marketing, HR, procurement, finance, sales, or IT operations
• Awareness of Responsible AI frameworks such as EU AI Act, NIST AI RMF, ISO/IEC 42001
• Hands-on familiarity with model evaluation, prompt evaluation, RAG architectures, MLOps concepts, and observability for AI systems
• Knowledge of partner platforms including agentic workflow tooling, hyperscaler AI platforms (AWS, Azure, Google Cloud), modern data platforms
• Consulting or comparable client-facing delivery experience
• Experience leading distributed and offshore teams, shaping deal pursuits, and developing junior talent at senior levels
• AI Product Academy certification
• Certified Scrum Product Owner (CSPO) or SAFe Product Owner/Product Manager (POPM)
• Hyperscaler AI/ML certifications (AWS, Microsoft Azure, Google Cloud)
• Responsible AI/AI governance credentials (e.g., IAPP AIGP)

Personal attributes:

• Analytical, pragmatic problem-solver; outcome-oriented
• Self-directed, able to prioritize and juggle multiple workstreams
• Clear communicator simplifying complexity for technical and non-technical audiences
• Comfortable with ambiguity and iteration in AI product development
• Collaborative, curious, continuous learner
• Confident voice on Responsible AI, willing to challenge and enable

• Shape AI use cases by identifying where machine learning, generative AI, and agentic AI can solve real business problems and where they cannot
• Frame business cases and value hypotheses for AI products, including success metrics, costs, risks, and dependencies
• Own and prioritize the AI product backlog, translating ambiguous opportunities into well-scoped, testable increments for data science and engineering teams
• Define product vision and roadmaps for AI-enabled products balancing experimentation with production-grade delivery
• Translate business problems into AI problems specifying data requirements, evaluation criteria, acceptance criteria, and guardrails for ML and GenAI features
• Advise on Responsible AI in product decisions including fairness, transparency, accountability, human oversight, and 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