Invest in your career with a Madrona-funded company.

Trek Health is the AI platform for payer performance. We help healthcare provider organizations — from independent physician groups to major health systems — turn reimbursement data, contracts, policies, and claims into intelligence they can act on. Our platform's AI agents power payer negotiations, contract analysis, policy monitoring, and underpayment detection for 130+ provider organizations, replacing weeks of manual analysis with answers in minutes. Customers have used Trek to increase inpatient reimbursement by 30% and cut contract research time by more than 80%.

We're a fast-growing, Series A company at the intersection of healthcare economics and applied AI — and we're building the team that brings this platform to every new customer.

Sales Engineers at Trek own the technical side of the sales cycle. Paired with an Account Executive, you are the person who deeply understands a prospect's use case, shows them exactly what Trek can do for their organization, and proves it with their own data. You'll run technical discovery, deliver demos that make executives lean forward, build proofs of concept, validate data, model ROI, and configure AI agents and skills tailored to each client's needs.

This is a role for someone who is equal parts consultant, analyst, and builder: persuasive in front of a room, rigorous with a dataset, and fluent with the newest AI models and agent frameworks. Your work directly determines whether a prospect becomes a customer — and how excited they are on day one.

• Technical discovery. Partner with AEs during the sales cycle to uncover each prospect's use case, workflows, data landscape, and success criteria — and translate what you learn into a winning technical strategy for the deal.
• Tailored demos. Demo the Trek platform in a way that maps directly to the client's needs and gets them excited about what they'll be able to do — including presenting specified demos and deliverables to large groups of executives.
• Proofs of concept. Scope, build, and deliver technical POCs that prove Trek's value on the prospect's own entities, use cases, and data, and carry them through to contract.
• Data validation. Go deep with the client's technical point of contact or analyst to validate that the data in our system for their entities looks right — the critical step before a client moves forward with us.
• ROI modeling. Build ROI and business-case models that quantify Trek's impact and give champions the numbers they need to sell internally.
• AI agents and skills. Configure AI agents, author skill files, and build custom client use cases on top of Trek's agent platform using the latest LLMs and models.
• Voice of the field. Feed what you learn from prospects back to product, marketing, and leadership to sharpen our platform and our pitch.



• Persuasive and client-facing. You've spent real time in front of clients in a consultative, persuasive capacity — in sales engineering, management consulting, banking, strategy & ops, or a similar role — and you know how to earn trust and move a room.
• Perceptive. You read people and organizations well: you pick up on what a client actually needs (not just what they say), sense where a deal stands, and adapt on the fly.
• Deeply analytical and detailed. You work fluently with data — finding trends and patterns in messy datasets and using them to drive your decision-making, strategy, and client recommendations. Nothing you present has an error in it.
• AI-forward. You have hands-on experience configuring AI agents and building AI skills with modern LLMs, and you're the kind of person who tries every new model the week it ships.
• A strong communicator. You can explain a technical concept to an analyst and a business case to a CFO — often in the same meeting — and produce crisp, executive-ready deliverables.
• Self-directed. You thrive with ownership and ambiguity, juggling multiple active deals and POCs at a startup's pace.

• Experience in healthcare — revenue cycle management, payer contracting, price transparency, claims data, or health-tech more broadly.
• Prior sales engineering, solutions consulting, or technical pre-sales experience at a data or SaaS company.
• Comfort with SQL, Python, or similar tools for working with data at scale.

Bay Area strongly preferred. Some travel to customers and industry events.