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A seed-stage AI startup seeks a Software Engineer to build automation solutions from messy operational data. As part of a highly skilled team, you'll engage in full-stack development to create features with Python and TypeScript, ensuring product quality and customer trust while shaping the company's future direction.
Join a seed-stage AI startup turning messy ops data into automation that actually works. Ex-Palantir team, $6.5M funded, real traction. Build full-stack, ship fast, and shape how AI gets used in the real world.
This isn't your typical frontend/backend role. We are looking for product-minded engineers. It's a chance to build core infrastructure for how AI gets used in real companies, handling messy edge cases and all.
The team (ex-Palantir, Stanford, Yale) is building a platform that turns unstructured operational chaos, Slack threads, emails, tickets, into structured, agent-ready workflows. They're already embedded in critical sales, support, and ops systems at enterprise customers.
This is early-stage in the best way: high trust, high autonomy, fast feedback loops, and a product that's already solving real pain. You'll work closely with founders and users, and your code won't just ship; it will shape the company's direction.
Everyone's building AI agents, but most are brittle, overconfident, and wrong. The missing piece is context: the institutional knowledge, messy edge cases, and hard-won processes that make businesses function. This team is solving that problem.
They're not building a thin wrapper around GPT. They're creating the connective tissue between enterprise reality and AI potential. As foundation models improve, the product becomes more useful, not less.
If you want to do high-leverage engineering, learn fast, and see your work in production within days, this is a rare opportunity that offers all three.
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