Account Executive (First US Sales Hire)

About The Job

This role is open in San Francisco right now. Harper is an AI career agent that works for you, the candidate. Skip the application form: just talk to Harper about where you are and what you want next, and Harper puts the strongest profiles directly in front of the client's US GTM lead.

Job Title

Account Executive, San Francisco (first dedicated US sales hire)

Compensation

Base $130,000–$150,000. On-target earnings $220,000–$250,000 (base + commission), commission uncapped. Medical, dental, vision, 401(k), unlimited vacation.

Location

San Francisco, on-site. Full-time. The team believes the fastest way to build from zero is together in the room, and expects a minimum of 60 hours per week.

Company Description

A specialized AI cloud founded in Seoul in 2020 and now expanding in San Francisco. It provisions and routes GPU capacity across multiple clusters and providers so AI teams get one platform to access, scale, and manage compute, from a single GPU to thousands: multi-provider procurement, full-stack cluster operations, and deep expertise in large-scale training. Customers include an Artificial Analysis Top-15 foundation model team, physical-AI startups, and research groups at Stanford, UC Berkeley, UCLA, NYU, and UMN. Series A, ~40 people, ~$17M raised, revenue up 3.4x year over year, scaling from 3,000 to 10,000 GPUs by Q4 2026.

The Role

You will be the first dedicated sales hire in the US. There is active pipeline, warm leads from events and inbound, and a product AI/ML teams already use. What is missing is someone whose full-time job is converting that pipeline into closed revenue. You own the entire funnel: qualifying inbound, running outbound with the US GTM Lead, discovery, proposals, procurement, and close. Deals are real, five to six figures, selling GPU compute to AI startups, research labs, and enterprise teams with immediate workload needs. GPU supply is tripling by Q4 2026, so what you can sell against grows faster than the team. Every deal you close is visible, and you write the playbook AE #2 will learn from.

What You'll Own

• Pipeline and deal execution: discovery calls that uncover real compute pain (quota limits, environment setup, multi-cloud fragmentation, cluster scaling), proposals mapped to the buyer's workload, procurement, pricing, close. Buyers are AI/ML engineers, ML platform leads, and research computing heads

• Outbound campaigns with the US GTM Lead: personalized sequences, multi-channel outreach, event follow-up cadences, turning booked meetings into pipeline

• PLG conversion: work with the Growth Marketer to spot high-potential accounts on the self-serve cloud and convert free usage into paid contracts

• CRM and sales infrastructure: own HubSpot end to end (stages, tracking, forecasting, reporting)

• AI as a multiplier: research, outreach, call prep, and admin compressed with AI tools; unlimited Claude Code tokens

Who You Are

• 3 to 5 years in B2B sales, ideally at an infrastructure, cloud, or developer-tools company

• A full-cycle closer who has navigated multi-stakeholder deals with technical buyers, procurement, and executive sponsors

• Comfortable building outbound from scratch; there is no SDR layer, no enablement team

• Able to hold a technical conversation about GPU infrastructure, cloud compute, or distributed training, and learn fast

• AI-native: you already compress hours of research and outreach into minutes

• Early-stage experience, or ready to leave the structure behind

Even better

• An existing network in the AI/ML or GPU compute ecosystem

• Prior sales to AI/ML engineers, research labs, academic institutions, or infrastructure buyers

Process

Application review → initial screen → hiring manager screen → take-home assignment → deep-dive interview → leadership interview → CEO interview → offer.

Why Join

• First US sales hire at a company tripling GPU supply this year: the quota is backed by capacity, not hope

• Uncapped commission on five- and six-figure deals, and a playbook you get to write

• A technical product AI teams already use, with inbound and event pipeline waiting