Member of Technical Staff, Agentic Systems
Required skills
- agent infrastructure
- orchestration
- tool calling
- retrieval over data catalogs
- retries and fallbacks
- human-in-the-loop review
- LLM applications
- tool use
- structured outputs
- evals
Nice to have
- healthcare data
- regulated data
- data governance
- access control
- code-generating agents
- data-analysis agents
Role summary
GenMD, a well-funded AI and data infrastructure company for healthcare, is seeking a Member of Technical Staff specializing in Agentic Systems. This role involves designing, building, and owning the production systems that power AI agents like Mira, an AI research assistant. Responsibilities include developing agent infrastructure, managing LLM applications, implementing evaluation systems, and designing secure data models and APIs for sensitive healthcare data. The ideal candidate has 3+ years of experience in production backend systems, proficiency in Python or TypeScript, and hands-on experience with LLM applications and cloud data infrastructure (GCP/BigQuery preferred). Experience with healthcare data governance is a plus.
About GenMD
GenMD is a Stanford spin-off building AI and data infrastructure for healthcare. We grew out of years of work inside Stanford Medicine, alongside world-class researchers and clinicians, and we now work with health systems and data partners on large longitudinal datasets: claims, health records, imaging and clinical notes. We make that data usable for researchers and frontier AI, while patient privacy stays protected.
We're just coming out of stealth, already revenue-generating and well funded. We're intentionally small, move fast, and are focused on building something fundamental. Our CEO is a former Associate Director of AI at Stanford Medicine. See how we work: https://genmd.ai/careers
About the role
A growing share of GenMD's product runs on agents, starting with Mira, our AI research assistant on Healthcare Datahub. Mira helps researchers find the right dataset, explore cohorts and write analysis code. You'll design and ship the systems those agents run on, and own them in production against real researchers and real data.
What you'll do
Build and own agent infrastructure: orchestration, tool calling, retrieval over data catalogs and dictionaries, retries and fallbacks, and human-in-the-loop review.
Ship agents into production and keep improving them against real usage: prompts, tools, guardrails, and cost and latency trade-offs.
Build evaluation for agents: offline evals, online metrics and regression detection that tell us whether an agent is actually working.
Design the services, data models and APIs that keep agent actions auditable, permissioned and safe around sensitive healthcare data.
Work directly with the founders, researchers and partners to decide what agents should do and where a human stays in the loop.
What we're looking for
3+ years building production backend systems; strong in Python or TypeScript.
Hands-on experience shipping LLM applications or agents (tool use, structured outputs, evals).
Experience with cloud data infrastructure (GCP/BigQuery preferred) and building secure, well-tested services.
You own systems end to end and move quickly without lowering the bar.
Nice to have
Experience with healthcare or other regulated data, data governance or access control.
Experience building code-generating or data-analysis agents.
Compensation
$180,000 – $250,000 per year, plus equity. Final offer depends on experience.
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