Sales Engineer [NYC]

Concurrence•New York, NY

7d•$170,000 - $200,000•Onsite

About The Position

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.

Requirements

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

Nice To Haves

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

Responsibilities

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