[Remote] Product Manager - AI and Data Products
Note: The job is a remote job and is open to candidates in USA. Stratus is the operating system for mechanical, electrical, and plumbing construction. They are hiring a Product Manager to build AI and data-driven products, focusing on turning large construction data sets into commercial products and durable data advantages.
Responsibilities
- 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
Skills
- Five-plus years in product management, including time at a B2B SaaS scale up
- You have built or shipped products using LLMs or agentic AI
- A track record of turning big data sets into commercial products
- B2B SaaS features you took to market that measurably moved adoption, revenue, or retention
- Comfort with data models, data pipelines, workflow software, integrations, and the engineering conversations that go with them
- 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
- 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
Company Overview