Senior Product Manager — AI-native construction intelligence Remote

The role sits between the engineering of AI harnesses — pipelines, agent orchestration, multi-model evals, systems grounded in the project record — and the people who run a site: general contractors, project managers, field engineers.
Set the sequence: field-capture processing, plan parsing, submittal review, cost, progress — and say which of those is a harness problem this quarter. Specify developer-facing and internal harnesses that bind LLMs and vision-language models to the project record, so a hallucination is a test failure rather than a site surprise. Stand up agents that can flag a hazard, follow a delivery, check a build against the drawing, or draft a change order — always with an eval attached. Go to site. Talk to project managers, superintendents and subcontractors. Write the bottleneck down before you write the ticket. Own the evals for accuracy, safety and reliability wherever the output can move money or injure someone. Work with the people who sell and support the work so hours saved, risk avoided and rework cut are measured, not asserted.
01What you will do
Set the sequence: field-capture processing, plan parsing, submittal review, cost, progress — and say which of those is a harness problem this quarter. Specify developer-facing and internal harnesses that bind LLMs and vision-language models to the project record, so a hallucination is a test failure rather than a site surprise. Stand up agents that can flag a hazard, follow a delivery, check a build against the drawing, or draft a change order — always with an eval attached. Go to site. Talk to project managers, superintendents and subcontractors. Write the bottleneck down before you write the ticket. Own the evals for accuracy, safety and reliability wherever the output can move money or injure someone. Work with the people who sell and support the work so hours saved, risk avoided and rework cut are measured, not asserted.
What you bring
Three or more years running AI or ML products: agent architectures, retrieval, computer vision, and an eval harness you have actually used. The construction lifecycle — pre-construction, bid, schedule, execute, handover — and the tools the trades already live in: Procore, Autodesk Construction Cloud, Primavera P6, Revit, OpenSpace. A plan for unstructured site data: photographs, 360 scans, drone footage, PDF specs, BIM metadata. Four or more years of product work in B2B software, PropTech, ConTech, or developer infrastructure. Interviews, prototypes, a backlog you will defend, and the ability to talk to researchers, engineers, designers and a superintendent in the same week.
02What you bring
Three or more years running AI or ML products: agent architectures, retrieval, computer vision, and an eval harness you have actually used. The construction lifecycle — pre-construction, bid, schedule, execute, handover — and the tools the trades already live in: Procore, Autodesk Construction Cloud, Primavera P6, Revit, OpenSpace. A plan for unstructured site data: photographs, 360 scans, drone footage, PDF specs, BIM metadata. Four or more years of product work in B2B software, PropTech, ConTech, or developer infrastructure. Interviews, prototypes, a backlog you will defend, and the ability to talk to researchers, engineers, designers and a superintendent in the same week.
Useful, not required
Civil engineering, construction management, architecture, or computer science as a first training. Prompting and model-eval tools (LangSmith, MLflow, a custom CLI) used as instruments, not as theatre. A zero-to-one AI product shipped into a trade that still runs on paper and a WhatsApp group.
03Useful, not required
Civil engineering, construction management, architecture, or computer science as a first training. Prompting and model-eval tools (LangSmith, MLflow, a custom CLI) used as instruments, not as theatre. A zero-to-one AI product shipped into a trade that still runs on paper and a WhatsApp group.
The first quarter
Run discovery on live accounts and audit the current models and their evals. Set the twelve-month map: which agentic workflows matter, and which harness gaps block them. Ship one feature — a plan-set delta check or live risk alert — with retention and accuracy defined before release.