AEC Product Lead

LightTable AI•Denver, CO

1d•$185,000 - $200,000

About The Position

LightTable builds AI that understands the documents behind large commercial and data center projects, helping the project teams make better decisions earlier. We recently closed the largest Series A investment round of any AI software company in Colorado history, and some of the world’s largest GCs and data center builders are actively using LightTable. We move fast, we care about the product fit, and we build with AI. We do this not just for our customers, but internally too. You’ll find a hard working team that gives you an incredible opportunity to quickly grow in your career. Every large project is a chain of decisions made with incomplete information, by people who can't see how one choice ripples into cost, schedule and risk somewhere else. You have lived that. As AEC Product Lead, you bring that experience to help our AI team decide what LightTable builds and how it all works. You are the AEC industry's voice in Product and Engineering. You know which decisions matter most on a project, the inputs that drive them and the team needed to make them well. You work with AI engineers so LightTable software reflects how projects are actually developed, designed, bought out and built. We are not automating the old process. We are building a new way to run projects, and you will help define what it looks like.

Requirements

Bachelor's or master's degree in architecture, engineering, construction management or a related field.
8+ years in architecture, engineering, or with a general contractor, owner/developer or owner's representative on large commercial, mission-critical or data center projects.
Lifecycle fluency: Hands-on work across more than one phase of a project, from feasibility and design through buyout, procurement, construction and turnover. You know how a decision in one phase becomes a cost, delay or dispute in another, and what information would have changed it.
Multi-stakeholder perspective: You understand the development process from more than one seat at the table, and why each party acts the way it does.
Document depth: You read drawings, specs, contracts, schedules and submittals as one connected picture, and you can tell a real problem from noise a project team will learn to ignore.
Product judgment: You have defined what a tool, process or standard should do and gotten it built, whether at a software company, in an internal technology group, or by driving firm-wide standards. You write clear problem statements and say no to the wrong solution.
Engineering partnership: Comfortable in technical conversations about data, logic and tradeoffs. You don't need to code, but you can reason about how a system interprets project information and predict where it will go wrong.
Customer discovery: Exceptional listening and questioning. You uncover the root problem beneath the stated request and separate what people say from what they do.
Communication: You translate practitioner insight into product direction and business value, and adapt the message for engineers, practitioners and executives.
AI conviction: Hands-on with AI. We’re looking for someone who thinks about how AI will change the way projects are run.

Nice To Haves

Professional licensure (RA, PE) or equivalent industry credentials.
Product management, product ownership or solutions experience at a construction technology company.
Owner or developer-side experience: feasibility, basis of design, procurement and contract decisions.
Data center or hyperscaler project experience, including MEP-heavy and OFCI-driven coordination.
Experience building firm standards, BIM execution plans or preconstruction programs at scale.
Fluency with the tools project teams already use: Bluebeam, Procore, Autodesk Construction Cloud, Revit, Navisworks, Primavera P6.
Familiarity with how AI systems are evaluated: precision, recall, test sets and what ground truth means in practice.

Responsibilities

Own the AEC side of the roadmap. Decide which problems across the project lifecycle are worth solving. Make the case to leadership and AI Engineering for what comes next. Iterate with AI engineers, where most of the thinking on what the product should do and what it implies is yours.
Turn AEC practice into software designs. Identify industry problems, domain logic and acceptance criteria engineers build against. When the question is "what should the product do, what do you want AI to solve?", you answer it.
Collaborate with Software Engineering. Join planning and reviews, test what's built against real project documents and real decisions, and judge whether an output is right, noisy or missing before a customer ever sees it.
Expand what the product understands. As LightTable takes on new document types, project phases and stakeholders, define successful outputs in practice: what a practitioner needs to see to act.
Go to the field. Sit with developers, contractors, architects and engineers on live projects. Watch how decisions really get made, where the product fits and bring back specific, prioritized input.
Run the feedback loop. Synthesize what AEC Specialists, Engagement Managers and Support learn across pilots and enterprise accounts. Own feedback log, route every gap with the stakeholders and documents that caused it, and close the loop with whoever raised it.
Own output quality. Define what right, wrong and missing mean for each capability, measure it on live accounts, and drive the changes that move it.
Equip Go-to-Market (Sales). Give the account executives and AEC Specialists the roadmap context, release notes and training they need to represent the product well, and join customer conversations as needed.
Shape the industry conversation. Represent LightTable with customers, partners and the wider AEC community as a practitioner who understands how the industry works today and where AI is taking it.