Description du poste
About Foresight
Foresight's mission is to bring the world's critical infrastructure into service faster by better enabling teams to deliver complex capital projects.
The AI buildout runs on physical things: data centers, power, and the supply chains behind them. A single hyperscale campus involves an owner, a general contractor, dozens of trades, long-lead equipment suppliers, lenders and commissioning teams. Each works from its own schedule and its own spreadsheets. When a project slips, the people who could fix it usually find out last. For an AI data center, a month late can mean tens of millions in lost revenue.
Foresight is the control tower for these projects. We connect schedules, field progress and execution data across every party, forecast where delivery is heading, and help teams act before a delay becomes a missed date. On one 15-project portfolio, Foresight found a project 245 days behind, cut reporting overhead by 90%, and helped prevent more than $100M in lost revenue.
We work with top data-center owners, developers and general contractors across the world, including Crusoe, Applied Digital, and NTT. We raised a $25M Series A led by Macquarie Capital and are headquartered in New York.
The role
We're looking for a
Senior Full Stack Engineer
to help build the core platform and product of Foresight.
You will build the systems that will enhance the ability for efficient delivery of large scale construction projects. You will design the APIs and data models that bring Foresight's risk predictions and AI recommendations into the product, and the interfaces that make 100k-activity projects understandable at a glance. This is a hands-on role on a new team, for someone who owns features from database to browser and builds systems that are accurate, scalable and observable.
At Foresight, full stack means you own the whole problem. You take complex, high-stakes project data and turn it into products that help teams deliver major projects on time. This could translate to work on:
Project intelligence: Build the interfaces and services that surface predicted delays, risk exposure and AI-recommended actions, so teams can act before problems land.
Schedule data teams can trust: Bring in data from the scheduling tools the industry runs on, keep a reliable history of every update, and show teams clearly what changed and why....