Agent Researcher

About Bunkerhill

Bunkerhill is a long-horizon agent for health system knowledge work. Health systems use our agent’s built-in capabilities for work that is performed consistently across customers, and use its tailored capabilities for work that is specific to them.

We are an in-person, in-office team in SF and NYC that exemplifies three core values: build for the patient, own it ship it, be bold together.

About the team

What makes health systems unique from other verticals adopting agents is the use of repetitive intelligence: the same closed-ended task is performed tens to hundreds of thousands of times per health system per year.

The team shapes the future of how our agents will be used by our customers years from now, informed by how they use them today.

About the role

• Inform optimal agent design through experimentation
• Optimize agentic correctness, cost, and velocity
• Increase agent developer velocity
• Establish reliable connectors with third-party systems
• Own agent testing and evaluation
• Identify and advocate for platform improvements
• Identify opportunities that demand repetitive intelligence

Your background

• Strong technical foundation: comfortable writing code, collaborating in technical teams, and understanding core agent concepts such as delegation, memories, tool-calling, compaction, structured outputs, context engineering, and prompt design
• Strong scientific background: comfortable running experiments and with AI fundamentals such as dataset curation, training an AI system, designing evaluations and metrics, error analysis, and drawing sound conclusions from noisy results

Even better

• Experience building AI systems or agentic systems
• A CS, engineering, or math degree or equivalent technical experience
• Experience with healthcare data or systems, such as EHRs, clinical documentation, or HL7/FHIR
• Experience taking an AI system from prototype to production at scale
• Published research or open-source contributions in machine learning or AI agents