Stratus is hiring a Product Manager to build our AI and data-driven products. This is a hands-on individual contributor role. You will own initiatives end to end, write the specs, sit shoulder to shoulder with engineering, and ship. You are a doer, not a manager of doers.

Your focus is taking large, messy construction data sets and turning them into commercial products and durable data advantages. That means agentic AI and LLM-powered workflows, productized data, and features that get better as more customers use them. You will work directly with engineering, design partners, and the executive team.

We care less about a candidate who can recite a process and more about one who knows how to make good calls when the path is not obvious. If you can listen well, write clearly, prioritize honestly, and ship work that customers actually adopt, you will do well here.

What You Will Own

• AI and data product initiatives end to end, from problem definition through spec, build, launch, and measurement, tied explicitly to ARR growth, retention, and adoption.

• Agentic AI and LLM-powered features, from concept to shipped product, with a clear point of view on where the technology creates real value and where it does not.

• Data productization. You turn large construction data sets into commercial products and build data advantages that compound as adoption grows.

• Crisp specs and PRDs that engineering can execute without rework, plus the day-to-day partnership with engineering to get them built.

• A working feedback loop with design partners, converting qualitative and usage signal into product decisions.

• Launch and adoption. You partner with PMM, sales, and CS so features land with customers, not just in the release notes.

What We Are Looking For

• SaaS scale-up experience. Five-plus years in product management, including time at a B2B SaaS scale up. This is our number one priority.

• Agentic AI and LLM experience. You have built or shipped products using LLMs or agentic AI, and you understand the practical realities of working with these tools in production.

• Data productization background. A track record of turning big data sets into commercial products. You have taken raw or messy data and made it into something customers pay for or rely on, and you understand how data advantages are built and defended.

• A shippingtrack record. B2B SaaS features you took to market that measurably moved adoption, revenue, or retention. You can talk through the metric, the move, and what you would do differently.

• Technical depth. Comfort with data models, data pipelines, workflow software, integrations, and the engineering conversations that go with them.

• Strong communication. Tight specs, concrete customer stories, short and decision-oriented updates.

• Mid to senior level. MEP, AEC, or construction technology background is a plus, not a requirement.

Nice to Have

• Experience building data moats or network-effect data products.

• Exposure to BIM tooling, ERP or accounting integrations, or other construction and industrial data sources.

• Experience standing up evals, retrieval pipelines, or model-backed features in a production product.

Interview Process

• 30 minute screen with Holly Katz, Talent.

• 45 minute conversation with Richard Calhoun, CPO.

• Panel Interviews PMM/Prod/Dev, etc.

• Final panel including a case study focused on an AI or data product problem. The panel includes the CPO and a cross functional leader.

Why This Seat Matters

Stratus is sitting on data that no one else in MEP construction has. This role exists to turn that into products customers cannot get anywhere else. You will own real surface area, with named customers and a clear line from your work to ARR, retention, and adoption. If you want to build AI and data products with immediate commercial impact rather than manage a backlog, this is the seat.

This is a remote role but candidates must be based in the United States.