Member of Technical Staff, Health Systems at Openevidence

Job description

OpenEvidence is the most widely used medical AI platform in the world. In just over a year, our usage has grown to >65% of US clinicians via product-led word of mouth adoption. We are a $12B company with a 30 person engineering team from MIT, Harvard, and Stanford. We believe world-changing products come from a small group of exceptional, autonomous builders, organized along focused objectives and empowered to take individual ownership and run fast. We are growing our team to seize a once-in-a-lifetime opportunity to define the default platform for medical AI. If you are a world-class engineer, looking to define the bleeding edge and deliver concrete outcomes that impact hundreds of millions of lives, we want to talk. Culture We believe work is something that should be engaged with at a world-class level. Building 0->1 and scaling 1->1000 are professional sports, and uncompromising excellence is the bar. We believe building technologies that haven't existed is only possible with end to end ownership. We don't have product managers–every engineer is responsible for landing major improvements to the product. Important things are accomplished when an individual decides to accomplish them. Who are you? The ideal candidate is a brilliant builder. They are smart, ambitious, scrappy, autonomous, precise, motivated, hard-working, and low-ego. Does that sound rare? It is rare, we have only found 30 of them, and we would like to find more. The role You will help design the future of OpenEvidence inside clinical workflows. As the technical and product lead for our health system partners, you will shape what OpenEvidence looks like when it is built into the places clinicians already work, and decide what we build next to get there. When clinicians or partners need something that does not exist yet, you will define it, build it, and see it through to launch. Some days you will write or review code. Other days you will prototype a new clinical workflow, set the technical direction for a launch, shape the product roadmap based on what you learn from clinicians and partners, or present your plans to health system IT, security, and clinical leaders. What you'll do - Lead how OpenEvidence is designed, built, and launched inside health systems, from product ideation through ongoing support. - Make product and architectural decisions, often in ambiguous situations. - Build enterprise product capabilities, and turn recurring needs into scalable tools and processes. - Uphold the high standards for security, privacy, and reliability that our health system partners expect. - Work across engineering, product, sales, support, legal, and partners to get it done. What we're looking for - 3+ years of professional engineering experience; 5+ years preferred. - A strong engineer with excellent product judgment - in particular around risk, reliability, and production changes. - The ability to understand complex systems and quickly find the real source of a problem. - Strong written and verbal communication skills, covering both sophisticated enterprise audiences and non-technical clinical leaders. - Preferred: Experience with health systems, EHR integrations, clinical AI benchmarketing, agentic workflows, and enterprise SaaS implementations. - Preferred Location: In-person San Francisco, Miami or remote for stellar candidates who are willing to travel often to meet with the team.

Requirements

Must-haves

OpenEvidence is the most widely used medical AI platform in the world.
Who are you?
Lead how OpenEvidence is designed, built, and launched inside health systems, from product ideation through ongoing support.
Make product and architectural decisions, often in ambiguous situations.
Build enterprise product capabilities, and turn recurring needs into scalable tools and processes.
Uphold the high standards for security, privacy, and reliability that our health system partners expect.
Work across engineering, product, sales, support, legal, and partners to get it done.
A strong engineer with excellent product judgment - in particular around risk, reliability, and production changes.
The ability to understand complex systems and quickly find the real source of a problem.
Strong written and verbal communication skills, covering both sophisticated enterprise audiences and non-technical clinical leaders.

Nice-to-haves

3+ years of professional engineering experience; 5+ years preferred.
Preferred: Experience with health systems, EHR integrations, clinical AI benchmarketing, agentic workflows, and enterprise SaaS implementations.
Preferred Location: In-person San Francisco, Miami or remote for stellar candidates who are willing to travel often to meet with the team.

Application prep

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