Platform Product Owner AI Enablement and Vendor

Platform Product Owner - AI Enablement and Vendor Experience

Role Purpose

Drive the delivery of agentic AI across the platform. This includes identifying use cases, ensuring data foundations, building, launching, and tracking value. Translate process pain points into well-scoped AI opportunities, ensure data is catalogued and production-ready before agent construction, and coordinate with enterprise architects and engineering managers for production deployment. Utilize tools like Claude Code, Microsoft Copilot, and modern AI orchestration frameworks for hands-on prototyping and building.

Key Responsibilities

AI Use Case Development & Pipeline

• Partner with use case owners and Global Process Leads to identify, qualify, and size AI opportunities across enterprise workflows.
• Maintain a sequenced AI use case pipeline aligned to the AI Transformation roadmap and OP priorities.

Data & Catalogue Enablement

• Define data requirements (sources, fields, quality thresholds) for reliable agent function.
• Own Data Catalogue entries as a mandatory gate before POC or build.
• Build and maintain semantic search and retrieval layers (vector databases, embedding pipelines) to support agent grounding.

Technical Delivery & Hands-On AI Development

• Co-own technical design of AI agents with architects and engineering managers, defining APIs, data flows, and integration patterns.
• Design and build RAG pipelines, multi-agent workflows, and orchestration logic using frameworks such as LangChain, LangGraph, LlamaIndex, or AutoGen.
• Fine-tune prompts and evaluate outputs across LLMs (GPT, Claude, Gemini, or open-source models) for business scenarios.
• Deploy AI solutions on cloud platforms (Azure, AWS, or GCP), applying responsible AI and governance practices.

Adoption & Value Tracking

• Own business readiness for each launch (stakeholder alignment, training, communication) and mitigate adoption risks.
• Define and track business KPIs (e.g., hours saved, error reduction) and technical KPIs (e.g., accuracy, latency) per agent.
• Report value realization to the Head of AI Enablement.

Requirements & Tech Stack

Skills & Experience

• Experience in product ownership, business analysis, or process improvement within a procurement, supply chain, or operations environment.
• Demonstrable hands-on daily use of AI tools (Claude, Copilot, ChatGPT or equivalent) to solve real work problems.
• Working proficiency in Python and SQL, sufficient to prototype and iterate on agent code.
• Comfortable reading datasets, writing basic SQL, and assessing quality.

Preferred

• Deeper agentic AI experience (multi-agent systems, tool use, prompt engineering) with at least one working prototype.
• Experience with Databricks, Snowflake, Spark, or similar data platforms.
• Experience deploying AI workloads on major cloud providers (Azure, AWS, or GCP).
• Hands-on experience with at least one AI orchestration framework (LangChain, LangGraph, LlamaIndex, or AutoGen).
• Practical understanding of RAG, embeddings, and vector databases.
• Familiarity with data catalog/lineage concepts, MCP (Model Context Protocol), or transformation/platform product roles in a large, matrixed organization.
• Experience with procurement processes and platforms (e.g., Source-to-Contract, Procure-to-Pay, or vendor management systems).