Executive Product Owner - Enterprise Knowledge

Overview

Own the product vision, roadmap and prioritised backlog for the Knowledge Fabric, the federated context layer that connects enterprise knowledge to people and AI agents, and make sure it is adopted and delivers value.

What you'll do

• Own the product vision, roadmap and prioritised backlog for the Knowledge Fabric platform.
• Drive product exploration (e.g. using design thinking and analytics) and formulate hypotheses to validate product strategy / design.
• Translate consumer and architecture needs into clear features and acceptance criteria for the context layer, retrieval and MCP services, and knowledge controls.
• Be accountable for end-to-end value delivery and product lifecycle management, including managing requirements lifecycle, production deployment and release day coordination and sign off.
• Assess and implement build vs buy decisions to enable platform and capability build.
• Act as the voice of the customer and business and translate this for the squad.
• Apply expertise to support prioritisation, balance trade-offs, and explore strategies to successfully achieve business and customer outcomes.
• Lead the onboarding of consuming agent teams across multiple harnesses, with clear documentation, service expectations and support.
• Define and report platform KPIs, including latency, relevance, token cost, availability and entitlement conformance.
• Work with the Chief Engineer to balance new capability, reliability, security and technical debt.
• Ensure entitlements, fine-grained permissions and agent-specific access controls are reflected in product requirements and evidenced for risk stakeholders.
• Coordinate roadmaps and dependencies with the Chief Data Office, Chief AI Office, End User Experience and the Knowledge Domain products.
• Track and report progress in bringing use cases and domains live on the Knowledge Fabric.
• Manage the squad's performance to defined objectives including OKR tracking, etc.
• Ensure all obligations across customer, regulatory, internal policy and process frameworks (e.g. GDF, PDDP, RiC) are fully met and satisfied.
• Identify, articulate and manage risks, dependencies and compliance across streams of work (e.g. customer propositions).

What you'll need

• Have owned technical platform, API or data products used by other engineering teams.
• Product strategy, vision setting, roadmap creation, and outcome-based prioritisation.
• Understand how AI agents, retrieval-augmented generation, graph network and LLM applications consume context, and what makes retrieval good.
• Ability to assess and implement build vs buy decisions to enable platform and capability build.
• Strong stakeholder engagement and product-thinking skills to translate business knowledge, policies, processes, and controls into reusable enterprise knowledge products.
• Can turn complex technical and risk requirements into clear priorities and acceptance criteria.
• Use data and metrics to make product decisions and demonstrate value.
• Understanding of risk, governance, compliance, and responsible AI principles in regulated environments.
• Can align multiple teams with competing priorities towards a shared roadmap.
• Build trusted working relationships with engineers, architects, risk partners and business teams.
• Bachelor's or Master's Degree in any stream.

Nice to have

• Experience in Model Context Protocol, agent platforms, search or data platforms, identity and access management, or cost optimisation for AI workloads.

Details

• Location: Bangalore.
• Advertising end date: 20/11/2026.