Summary
✨ AI‑Generated
An early-career software engineering role for candidates with 0–2 years of professional experience, including strong interns and recent graduates. You will turn architectural designs into tested and documented software, collaborate closely with experienced engineers, and have structured opportunities to grow into broader engineering responsibilities.
Highlights
Early-career opportunity with built-in mentorship, clearly scoped work, rapid learning, meaningful projects, and a defined path for career progression.
Description
The Role
We're hiring Software Engineers to join FLINT's Intelligence team.
This is an early-career position, designed for someone with 0–2 years of professional experience (recent graduates and strong interns welcome) who wants to grow fast by building things that matter.
Software Engineers at FLINT work alongside our Forward Deployed Engineers (FDEs).
FDEs sit with the business, elicit requirements, and own the design and architecture of what we build.
Software Engineers take that design and turn it into working, tested, documented software on Foundry — and push back when the design doesn't hold up.
You'll have a clear owner to learn from and a steady stream of well-scoped work to ship.
This is a foundational role with mentorship built in and a defined path forward — first through the Software Engineer levels, and then, for those who develop real fluency in how FLINT operates, into the Forward Deployed Engineer track.
AI-Native by Default
We believe the teams moving fastest right now are the ones where AI is doing the bulk of the code writing, testing, and drafting, with engineers directing and verifying the work rather than typing it out.
We're building FLINT's Intelligence team that way, and we screen for it.
What AI-native looks like here:
You start from a spec, not a blank editor.
You use AI tools to draft, generate, and refactor code, then read it critically.You use AI to test at scale — generating scenarios, edge cases, and validation you'd never have time to write by hand.You treat your AI session as a production surface and Foundry as the system of record: work happens in the session, results land in the system.You can explain what the AI did, why it's right, and where it's wrong.
Speed without judgment doesn't count.If this is already how you work, you'll feel at home.
If you're curious but haven't built this way yet, tell us — we'd rather teach a curious engineer than hire a fast one who won't learn.
What You'll Do
Build applications, workflows, and pipelines on Palantir Foundry that make FLINT's data accessible, reliable, and actionable for project and manufacturing teams.Write and maintain Python to transform, clean, normalize, and connect data from the systems we run the company on — Autodesk Construction Cloud, Revit, Revizto, Oracle Primavera Cloud, and Sage Intacct, among others.Work with APIs and common data formats (JSON, CSV, XML) to integrate systems and automate processes end to end.Take well-defined work from FDEs and deliver it to a clear definition of done — then ask the questions that make the next definition better.Contribute to FLINT's ontology: the objects, relationships, and standards that let knowledge compound across projects.Document code, workflows, and applications so the team (and the company) can build on what you built.Support release cycles to beta testers in the field, and fold their feedback back into the build.What We're Looking For
0–2 years of professional experience coding in Python (internships and substantial personal projects count).Demonstrated AI-native working habits: you can show us how you use AI tools to design, build, and test software, and how you verify the output.Experience with data transformation and cleaning using libraries such as pandas, PySpark, or NumPy.Working understanding of common data formats (JSON, CSV, XML) and of consuming APIs for programmatic data exchange.Comfort with version control (Git) and with reading code you didn't write.Strong debugging, troubleshooting, and problem-solving skills.Genuine interest in construction, manufacturing, or the built environment — or at minimum, in learning how a real operating business works.