Senior Manager, Enterprise AI Product Management

Experience: 7 to 8 years in data, software, or AI, with at least 4 years of product management.

Reports to: Associate Director, Enterprise AI and Product Strategy.

Function: Enterprise AI, Product, and Market Strategy.

About the role:

KPI Partners is growing its portfolio of agentic AI products and AI-enabled data accelerators, and the current product leader needs a strong partner to run a meaningful share of that portfolio day to day.

In this role you will own the requirements, backlog, and release readiness for a set of products, and you will work every day with architects and engineers to turn client problems into working software.

This is a hands-on role for someone who wants to grow into a portfolio leader.

What you will do:

- Own the product backlog for one or more agentic domain products or data accelerators, and keep priorities clear for architects and engineers.

- Write detailed product requirements, user stories, and acceptance criteria that engineers can build from without repeated clarification.

- Run sprint planning, backlog refinement, and release reviews as the product owner, and track delivery against the roadmap.

- Gather requirements from client conversations, workshops, and subject matter experts, and translate what you hear into product decisions that you can explain and defend.

- Help define evaluation criteria for agents, including accuracy and groundedness benchmarks, and coordinate structured review sessions with subject matter experts before each release.

- Prepare and deliver solution demos for pursuits, and support proposal teams with accurate product content and realistic scope.

- Research the market, compare competing tools, and prepare build-versus-buy inputs that the Associate Director can take to the CEO.

- Work with marketing on product collateral, decks, and web content, and make sure every claim in that material is accurate and can be supported.

- Gather feedback from delivery teams and clients after each engagement, and turn it into improvements for the next release.

What you bring:

- About 7 to 8 years of experience in data, software, or AI, including at least 4 years in product management, product ownership, or a closely related solution role.

- Written requirements for data or AI products that engineering teams built and released, and ability to describe your own contribution clearly.

- Understanding of data engineering concepts such as ingestion, transformation, data quality, and warehouse design, and familiarity with at least one of Databricks, Snowflake, or Azure.

- Understanding of the basics of generative AI products, including retrieval-augmented generation, agents, prompt design, and evaluation.

- Clear written communication, ability to present well to clients and senior leaders, and ability to ask direct questions when something is unclear.

- Comfort with tools such as Jira, Azure DevOps, or Aha!, and ability to work with SQL well enough to check data and outputs yourself.

- Degree in engineering, technology, or a related field; MBA or product management certification is an advantage.

What will set you apart:

- Experience in a consulting or systems integration environment supporting pre-sales and delivery.

- Hands-on experience with agent frameworks, Model Context Protocol, text-to-SQL tools, or model routing.

- Experience prototyping ideas yourself using modern AI-assisted tools.

- Experience in retail, life sciences, insurance, industrial, or consumer industries.

What success looks like in the first year:

- Within three months, understand the product portfolio well enough to run demos and client discussions with minimal support.

- Within six months, own the backlog and release readiness for at least one product and deliver a release that meets our evaluation standard.

- Within twelve months, be recognized by engineering and pre-sales as the person who turns client needs into clear, buildable requirements, and be ready to take on a broader portfolio.