Lead development of production agentic AI systems: reasoning, planning, tool orchestration, memory and grounding, evaluation frameworks, and multimodal agent coordination across chat, voice, and UI. Translate research into reliable, testable systems and iterate with founders and customers.
Mission
About the Role
What You’ll Do
What You’ll Bring
Bonus
What We Offer
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.
About the Role
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.
• Design and implement reasoning and planning systems for real production workflows
• Build robust tool orchestration, grounding, and execution frameworks
• Develop memory, context, and state management for long-horizon tasks
• Create evaluation systems that measure correctness, reliability, and performance
• Work across chat, voice, and UI-based agents to make them coordinated and dependable
• Translate research ideas into production systems
• Partner closely with founders and customers to iterate quickly and ship
• Help define engineering culture, standards, and early technical direction
• 5+ years of software engineering experience
• 2+ years building and shipping LLM or agentic systems in production
• Experience with evals, memory, retrieval, and grounding architectures
• Comfort operating in ambiguous, open-ended problem spaces
• Strong bias toward building reliable, measurable, testable systems
• Product intuition - you care about real users and real outcomes
• Clear communication and strong collaboration skills
• Experience with fine-tuning or reinforcement learning
• Experience building multimodal agents (voice, computer-use)
• Experience in healthcare or other regulated environments
• Founding-level ownership and impact
• Competitive compensation with meaningful equity
• Direct access to founders and customers
• The opportunity to ship production systems in high-stakes environments
We’re based in San Francisco and prefer working in person, but are flexible for exceptional remote candidates. Visa sponsorship available.
Similar Jobs
Fintech • Financial Services
Serve as primary branch contact for consumer and business customers: acquire and grow relationships, recommend deposit/credit/investment solutions, resolve account inquiries, drive digital adoption, coordinate referrals to Wealth/Home Lending/Business Banking, and maintain compliance with documentation, licensing, and risk policies. Temporary licensed- pending role transitions to fully licensed Relationship Banker upon meeting FINRA/SAFE requirements.
Artificial Intelligence • Automotive • Greentech • Information Technology • Machine Learning • Software • Cybersecurity
Serves as chief of staff and strategic partner to a senior Sales leader, setting priorities and driving execution. Leads cross-functional sales transformation, productivity, process improvement, competitive response, and organizational change initiatives. Develops executive presentations and data-driven recommendations, aligns Sales, Marketing, Product, Finance, and business partners, and maintains scalable sales processes and playbooks. Leads and mentors Senior Managers and Managers while ensuring initiatives deliver measurable results.
Top Skills:
AIExcelMicrosoft OutlookMicrosoft PowerpointMicrosoft WordSalesforceSalesforce Enterprise Territory ManagementSnowflake
Gaming
Develop and deploy slot-game features in Unity and C#, including gameplay, UI/UX, engine systems, and creator tools. Build server-backend functionality, investigate and extend slot-engine systems, define technical tasks, and quickly resolve bugs. The role requires collaboration, strong communication, and delivery under deadlines, with opportunities to work on live mobile games and performance optimization.
Top Skills:
C#GitPHPUnity
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
