Sales Engineer [NYC]

Concurrence (formerly Amigo) is building the platform healthcare organizations use to build their own clinical AI agents. Our mission is to make excellent care accessible to every patient, not rationed by the limits of clinician time.

Underneath our platform is the Health World Model, which unifies a health system’s data into a living, event-level record of every patient’s care. On top of it, agents handle work across the patient journey, from intake and scheduling to medication management and clinical decision support.

Our agents have supported more than 10 million patient encounters and are on track to grow tenfold this year. We run natively on Databricks, integrate with every major EHR, and are backed by Madrona, General Catalyst, and Optum Ventures. We’re about 35 people, working in person in New York and San Francisco.

As a Sales Engineer at Concurrence, you'll own the technical side of a deal from first conversation through signature. You'll work alongside the account executive with CIOs, chief medical officers, and their teams, establish what their environment supports, and build the demo that proves it. It's a hands-on role: our sales engineers write code, and the job is to show a prospect what's possible, not only what already exists.

The role exists so our Applied AI Engineers can stay focused on production deployments. You own the pre-sales technical surface: scoping what we can do, building proof-of-concept agents, running technical discovery, and making the product feel real before anything is signed.

You'll often be the only technical person in the room, so the role suits someone who can carry that without support. The standard we work to is that a demo should hold up as a product rather than a services engagement.

We're building the team around two complementary strengths, and we'd rather someone be excellent at one than adequate at both. The first is building: you'd rather prototype five ideas in a week than polish one for a month, and you're happy being the first person to try the platform in a clinical domain we haven't touched. The second is domain depth: understanding how health systems operate, who signs, and who blocks. Over time we want coverage across the ecosystems our customers run on, including Epic, Cerner, Salesforce, and on-premise deployments.

• Build rapid POCs and demo environments tailored to specific prospect workflows and clinical use cases

• Partner with account executives during technical discovery to scope what's possible and shape deal architecture

• Design and deliver live technical demonstrations that translate prospect pain points into working agent experiences

• Prototype experimental agent configurations that explore new use cases and push the boundaries of what our platform can do

• Run technical deep dives with prospect clinical, IT, and operations teams to understand integration requirements and workflow constraints, including EHRs and payor systems we haven't worked with before

• Create reusable demo assets and POC templates that accelerate future sales cycles

• Write the reference architectures, pricing and sizing models, and persona maps our cloud and data partners need to put us in front of their field teams

• Translate technical objections into solutions during the sales process, including security, compliance, and integration feasibility

• Collaborate with Applied AI Engineers to hand off won deals cleanly, documenting POC learnings and customer expectations

• Feed insights from the field back to product and engineering: what prospects are asking for, what patterns emerge, and where the platform should go next

• Stay current on AI and LLM developments and competitor capabilities

• Experience in sales engineering, solutions engineering, or a 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. You can build a working prototype, not just talk about one, and you're proficient in Python

• Experience with LLMs, prompt engineering, and building on AI platforms

• A hacker mentality: you're fast, scrappy, and energized by building things from scratch under time pressure

• Genuine excitement for AI innovation and exploring experimental use cases. You follow the space obsessively

• Ability to run a room, presenting to technical and executive audiences, handling objections live, and thinking on your feet

• Strong discovery skills: you ask the right questions to uncover real problems, not just stated requirements

• Experience working deals alongside account executives, and an understanding of sales cycles and buyer psychology

• Clear technical communication. You can explain complex systems to non-technical stakeholders without dumbing it down

• Comfort with ambiguity: prospects don't hand you clean requirements, and you thrive in that environment

• You're low ego, direct, and hold yourself to a high bar

• You can work on site in New York City

• Experience in healthcare technology or another regulated industry

• Background as a software engineer who moved into a customer-facing role, or the reverse

• Deep knowledge of one ecosystem we sell into (Epic, Cerner, Salesforce, on-premise health systems), including how those organizations buy

• Familiarity with healthcare workflows, clinical terminology, and 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 the latency and 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

• A track record of directly influencing deal outcomes through technical work

• Comprehensive health, dental, and vision insurance

• Daily catered lunch and dinner

• Mental health support and wellness coaching

• Flexible wellness stipend for fitness, therapy, or personal growth

• Annual learning budget for courses, books, or conferences

• Conference attendance budget for professional development

• Annual team offsite

• Academic collaboration opportunities

• Unlimited PTO

1. Patients Win, We Win

   If patients aren't getting better care, we haven't earned the right to scale. Every internal decision gets pressure-tested: does this make patients' lives better? If we can't draw the line, we question why we're doing it.

2. High Standards, High Care

   We hold a high bar for the team because patients are counting on us to get this right. But high standards only work with genuine investment in each other. You can take risks, admit mistakes, and challenge ideas. Not despite our standards, but because of them.

3. Thoughtful Urgency

   We move fast by default, but speed without judgment is recklessness. The discipline is knowing which decisions are reversible vs. not. In healthcare AI, the companies that win will be fast everywhere they can be and careful everywhere they must be. We build the muscle to do both.

4. Intensely Measured

   We instrument patient outcomes, provider ROI, system performance, and clinical accuracy. But data without action is surveillance. Every metric should have an owner, a threshold, and a response plan. If we're measuring something but never acting on it, we stop measuring it.

• Low ego: Politics and territory don't interest you. The best ideas win, regardless of who has them.

• Direct: You say the hard thing, challenge ideas openly, and commit fully once decided.

• High agency: You thrive on trust rather than instruction. When you see something is broken, you fix it. You don’t file tickets and wait for someone else.

• Bar of excellence: You hold yourself to a bar most people wouldn't, and you want teammates who do the same.

• Skeptical: You push back on rules that don’t make sense and question assumptions that haven’t earned their place.