Hike Medical

AI Account Executive

San Francisco, CA

Sponsorship not specified$120k-$200kDetected 35 days ago

Agentic AIHubSpotSalesAccount ManagementLeadershipCollaboration

About the role

SDRs hand you qualified demos with O&P clinics, Podiatry practices, Physical Therapy centers, and independent DME providers - and you turn them into live, paying accounts.
These are high-value providers running on analog workflows, which means large deals that move fast.
You'll sell the platform, not a single product: leading with the pain a prospect feels most and framing the whole road behind it.

As an Account Executive, you own the close.
Your job is to run a compelling demo, build the business case, and land the first paid order-then set the account up to grow.
Own the full cycle. Lead discovery, multi-thread across owners, clinicians, and revenue leads, walk the order form, and land the first paid order.
Forecast with discipline. Own an accurate pipeline in HubSpot and call your number with confidence.
Hike Intelligence - AI agents that run the revenue cycle, reading every faxed referral, verifying eligibility, chasing documents, and building audit-ready cases before a human touches a keyboard.
Hike Lab - our own 3D-printing factory, turning a scan into a custom, PDAC-approved device shipped in days, not weeks.
You know how to create urgency, handle objections, and ask for the order.

Strong base ($120K-$200K) + uncapped commission, with a roughly 50/50 base/variable split ($250K-$350K OTE).

Meaningful equity.
Full benefits.
Medical, dental, and vision coverage.
$15K relocation bonus.
2-4 years of closing experience, ideally selling AI, software, or into complex or owner-operated businesses (medical, dental, SaaS, or similar).
You can speak fluently about denials, reimbursement, and workflow-and earn the trust of a clinician and a revenue lead in the same call.

We're not filling a seat-we're looking for legends who can carry a number and own a region.

This listing is sourced directly from Hike Medical's careers page and normalized into a canonical job model.