Senior Product Manager, Enterprise Inventory Services

Sr Product Manager

Cox Automotive's Enterprise Inventory Services (EIS) team builds and operates the Common Vehicle Inventory (CVI) platform, the capability that powers vehicle inventory across Cox Automotive's retail products. CVI connects inventory data between dealer solutions, consumer-facing sites and operational tools used by internal teams. This is enterprise platform product management: you own capabilities that other products depend on.

We are hiring a Senior Product Manager to own a portfolio of inventory capabilities from problem discovery through adoption. You will define what to build and why, drive alignment across product, engineering, architecture, and UX, and ensure that what ships actually gets adopted by the teams and systems that depend on it. You will work across client segments, OEM programs, and internal operations to understand how inventory data flows and where it breaks.

This role requires someone who operates independently, thinks in outcomes rather than features, and brings a structured approach to discovery and prioritization. You will be accountable for the health of your discovery pipeline, the quality of your specs, and the adoption of what you ship. Product defines the problem and requirements.

Problem Discovery and Product Strategy. You lead discovery for your product area. That means identifying and validating problems through direct engagement with internal customers (operations, support, business stakeholders) and external clients (dealers, OEMs, integration partners). You define personas, map workflows, build hypotheses, and test them. You use data, customer evidence, and competitive context to form a point of view on what to build next, and you defend that point of view with specifics.

Discovery is not requirements gathering; it is structured problem-solving that produces conviction.

Spec-Driven Development. You write product discovery specs that clearly define the who, why, and what. Your specs include measurable acceptance criteria, defined scope boundaries, and enough context for a human or machine to evaluate feasibility and propose solutions. You own the quality of what enters the development pipeline.

Backlog Health and Pipeline Management. You maintain a forward-looking pipeline of meaningful work for your engineering teams. Your teams should always know what is coming next and why. You also exercise judgment about how far ahead to plan; in an AI-driven development environment, planning too far out creates waste. The right balance is enough runway to maintain momentum without over committing to solutions that may shift.

Cross-Functional Alignment. You navigate a matrixed environment where leaders have competing priorities. You build consensus by leading with evidence and framing tradeoffs clearly. You work across product, UX, engineering, architecture, business leadership, and solution delivery teams daily. You communicate headlines first, provide context second, and make it easy for leaders to make decisions.

Adoption and Go-to-Market for Platform Capabilities. Shipping is not success; adoption is. You define what complete adoption looks like for each capability, build rollout plans with implementation partners and operations, and track progress against measurable criteria. You treat internal customers with the same rigor as external ones.

Stakeholder Communication and Transparency. You surface status, risks, and wins proactively. You do not wait to be asked. You keep your manager and cross-functional partners informed at the right cadence with the right level of detail. When something is off track, you bring the problem and a recommended path forward, not just the problem.

Structured Discovery Skills. You have a repeatable playbook for moving from ambiguity to conviction. You can describe your methods and explain when you use each one. You know when to stop exploring and start committing.

Strategic Prioritization with Tradeoffs. You can articulate what you chose to build, what you chose not to build, and why. You connect your priorities to business outcomes, not just feature requests. You plan around outcomes and adjust when priorities shift. You balance long-term enterprise needs with short-term incremental value.

Data-Driven Decision Making. You anchor recommendations in evidence: usage data, customer feedback, operational metrics, cost analysis. When data is incomplete, you name what you know, what you are assuming, and what you would need to confirm.

AI Fluency. You use AI tools in your daily product work. You have integrated AI into discovery, analysis, spec writing, or prototyping in ways that change how you work. You have a point of view on how AI is changing the product management discipline and what becomes more (and less) important as AI capabilities expand.

Ownership and Accountability. You own outcomes, not activities. You meet deadlines and follow through on commitments without being chased. When you identify a problem, you…