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Concurrence is building clinical AI infrastructure that health systems, life sciences companies, payors, and government agencies use to deliver patient-facing care. The platform runs AI agents across the patient journey—pre-visit intake, care navigation, post-visit care plans, and ongoing monitoring—with the goal of making excellent care accessible to every patient rather than rationed by clinician time. Unlike point solutions or single-purpose chatbots, Concurrence rebuilds the medical record as a timeline of clinical events and runs agents on top that improve with every interaction. The company has supported over 10 million patient encounters and is on track to grow tenfold this year, backed by Tier 1 VCs including Madrona, General Catalyst, and Optum Ventures. The team is ~35 people working in-person in New York City and San Francisco.
As a Sales Engineer, you will own the technical side of deals from first conversation through signature, working alongside account executives with CIOs, chief medical officers, and their teams. You'll establish what their environment supports and build demos that prove what's possible. This is a hands-on role: sales engineers write code and show prospects what's achievable, not just what already exists. Your responsibilities include building rapid POCs and demo environments tailored to prospect workflows; partnering with account executives during technical discovery to scope capabilities and shape deal architecture; designing and delivering live technical demonstrations that translate pain points into working agent experiences; prototyping experimental agent configurations; running technical deep dives with prospect clinical, IT, and operations teams to understand integration requirements across EHRs and payor systems; creating reusable demo assets and POC templates; writing reference architectures, pricing models, and persona maps for cloud and data partners; translating technical objections into solutions around security, compliance, and integration feasibility; collaborating with Applied AI Engineers to hand off won deals cleanly; and feeding field insights back to product and engineering on what prospects need and where the platform should evolve. You'll stay current on AI, LLM developments, and competitor capabilities.
The role suits someone who can carry the technical surface alone without support, and the team is built around two complementary strengths: the first is building—prototyping five ideas in a week rather than polishing one for a month, and being the first to try the platform in new clinical domains; the second is domain depth—understanding how health systems operate, who signs, and who blocks. Over time, coverage across ecosystems including Epic, Cerner, Salesforce, and on-premise deployments is desired.
REQUIREMENTS:
- Experience in sales engineering, solutions engineering, or technical pre-sales role at a SaaS or AI company, with deals you can point to and describe your own technical contribution on
- Strong hands-on coding ability; can build a working prototype, not just talk about one; proficient in Python
- Experience with LLMs, prompt engineering, and building on AI platforms
- Hacker mentality: fast, scrappy, energized by building from scratch under time pressure
- Genuine excitement for AI innovation and exploring experimental use cases; follow the space obsessively
- Ability to run a room, presenting to technical and executive audiences, handling objections live, thinking on your feet
- Strong discovery skills: ask the right questions to uncover real problems, not just stated requirements
- Experience working deals alongside account executives; understanding of sales cycles and buyer psychology
- Clear technical communication; explain complex systems to non-technical stakeholders without dumbing it down
- Comfort with ambiguity; thrive when prospects don't hand you clean requirements
- Low ego, direct, hold yourself to a high bar
NICE TO HAVE:
- Experience in healthcare technology or another regulated industry
- Background as software engineer who moved into customer-facing role, or reverse
- Deep knowledge of one ecosystem (Epic, Cerner, Salesforce, on-premise health systems), including how those organizations buy
- Familiarity with healthcare workflows, clinical terminology, interoperability standards such as FHIR
- Understanding of healthcare compliance requirements such as HIPAA and SOC 2
- Experience building demo environments or sandbox platforms
- Experience with voice agents and latency/quality tradeoffs in speech-to-text and text-to-speech
- Experience building cloud partner motions such as AWS or GCP marketplace listings and joint reference architectures
- Track record of directly influencing deal outcomes through technical work
