Staff Engineer, Agentic Systems — Production AI

GenMD; Palo Alto (CA); On-site; USD 180,000 - 250,000; Full time

Benefits offered by this job

Equity

Job summary

GenMD, a Stanford spin-off, is hiring to design and ship agent infrastructure for the Healthcare Datahub. You will own the systems that run AI researchers' assistants, focusing on orchestration, tool use, data catalogs, retries, and human-in-the-loop review.

You will collaborate with founders, researchers and partners to decide agent tasks, implement secure production services on cloud data infrastructure (GCP/BigQuery), and optimize prompts, tools, guardrails, latency and cost.

Qualifications

• 3+ years building production backend systems.
• Hands-on experience shipping LLM applications or agents.
• Experience with cloud data infrastructure (GCP/BigQuery) and building secure, well-tested services.
• Own systems end to end and move quickly without lowering the bar.

Responsibilities

• 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.
• 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.

Skills

Python

TypeScript

LLM Agents

Cloud Data Infra

Tools

GCP

BigQuery

Job description

GenMD, a Stanford spin-off, is hiring to design and ship agent infrastructure for the Healthcare Datahub. You will own the systems that run AI researchers' assistants, focusing on orchestration, tool use, data catalogs, retries, and human-in-the-loop review.

You will collaborate with founders, researchers and partners to decide agent tasks, implement secure production services on cloud data infrastructure (GCP/BigQuery), and optimize prompts, tools, guardrails, latency and cost.