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If you ask a hospital today how much a treatment will cost, the answer is usually: “We don’t know.”
Not because providers don’t want to tell you but because patient cost is computed across insurance plans, negotiated rates, and billing rules that are fragmented, opaque, and not designed for real-time transparency.
What should be a simple question requires navigating a web of systems that don’t talk to each other.
So humans do that work instead.
They log into portals, call payers, follow decision trees, and manually stitch together answers across disconnected systems. Even when providers want to give a clear answer, the system makes it nearly impossible.
At Bravebird, we’re changing that.
We’re building agents that do the work between systems - end to end.
We believe the future of work is machines talking to machines, handling fragmented, system-to-system workflows so humans can focus on decisions, judgment, and care.
We’re building agentic AI systems that can reason, act, and operate reliably in messy, real-world environments - across chat, voice, and full computer-use interfaces.
As a Founding Engineer (Applied ML), you’ll help build the core intelligence powering these systems: reasoning, planning, grounding, memory, evaluation, and reliability.
This is a deeply technical, high-ownership role. You’ll work directly with founders, shape the technical direction, and ship systems that are used in real-world, high-stakes environments.
We’re based in San Francisco and prefer working in person, but are flexible for exceptional remote candidates. Visa sponsorship available.