Account Executive

AI researchers spend more time fighting for compute than doing research. Quota walls, rigid contracts, and fragmented supply across clouds and clusters mean teams are stuck waiting on a single provider that can't meet their needs.

VESSL AI was built to fix that. We provision and route GPU capacity across multiple clusters and providers, giving AI teams one platform to access, scale, and manage compute, from a single GPU to thousands. Multi-provider procurement so you're never locked to one source. Full-stack cluster operations from build to production. Deep domain expertise in large-scale training optimization.

We serve top research labs, academic institutions, AI startups, and enterprise teams globally. Customers include an Artificial Analysis Top 15 foundation model team, Physical AI startups, and research groups at Stanford, UC Berkeley, UMN, UCLA, NYU, and more. Founded in Seoul, South Korea, now expanding to San Francisco. Series A, ~40 people, scaling from 3,000 to 10,000 GPUs by Q4 2026.

• You will be the first dedicated sales hire in the US. We have active pipeline, warm leads from events and inbound, and a product that AI/ML teams are already using. What we don't have is someone whose full-time job is converting that pipeline into closed revenue.

• That's you. You'll own the entire sales funnel: qualifying inbound leads, running outbound campaigns with the US GTM Lead, conducting discovery, building proposals, navigating procurement, and closing. The deals are real, five to six figures, selling GPU compute to AI startups, research labs, and enterprise teams who have immediate workload needs.

• This is a high-upside role at a company where sales is just getting started. We're tripling GPU capacity by Q4 2026. That means the supply you can sell against is growing faster than the team. Every deal you close is visible. Your commission isn't capped. And as the US revenue grows, you'll have built the playbook that defines how VESSL sells.

• You'll work with the US GTM Lead and the rest of the US GTM team to scale VESSL's US revenue.

In your first 90 days, you'll take ownership of VESSL's active US pipeline and start closing. By month 3, you'll have active deals in late stages and a repeatable outbound motion generating new pipeline. By month 6, you'll have a predictable pipeline and a clear path to quota.

• Pipeline Ownership & Deal Execution

  • We have leads. Event contacts, inbound sign-ups, warm introductions. Your job is to qualify them, move them through the funnel, and close. You own the full lifecycle: discovery calls that uncover real compute pain (quota limits, environment setup, multi-cloud fragmentation, cluster scaling), proposals that map VESSL's capabilities to the buyer's workload, procurement navigation, pricing negotiation, and close. The buyers you're selling to are AI/ML engineers, ML platform leads, and research computing heads.

• Outbound Campaigns

  • Work with the US GTM Lead to design and run outbound campaigns targeting AI/ML infrastructure buyers. Prospecting sequences, multi-channel outreach (email, LinkedIn, calls), and event follow-up cadences. You're not doing this alone, but you are the one turning outbound into booked meetings and booked meetings into pipeline. AI startups, research labs, university compute teams, and enterprise AI groups are all in play.

• PLG Conversion

  • Work with the Growth Marketer to identify high-potential accounts on cloud.vessl.ai. Reach out to active users at the right moment and convert free usage into paid contracts. You care about usage patterns and activation signals, not just who filled out a form.

• CRM & Sales Infrastructure

  • Own the CRM (HubSpot). Pipeline stages, deal tracking, forecasting, and reporting. This is the system you'll build the sales playbook on. When we hire AE #2, they'll learn how to sell at VESSL from the system you built.

• AI as a Multiplier

  • Use AI tools (Claude, automation platforms, enrichment tools) to research accounts, draft outreach, prep for calls, and compress admin work. You see AI as the way a single AE operates at the output of a three-person sales team. We give you unlimited Claude Code tokens. The stage is yours.

• You have 3 to 5 years in B2B sales, ideally at an infrastructure, cloud, or developer tools company. You thrive in ambiguity. You've sold in environments where the playbook didn't exist yet, where pricing was still being figured out, where you had to find the right customers before you could close them.

• You know how to close. You've run full-cycle deals from first conversation to signed contract. You've navigated multi-stakeholder sales cycles with technical buyers, procurement, and executive sponsors. You know how to identify the person who can actually sign vs. the person who's just interested.

• You're comfortable with outbound. You can work with the GTM Lead on campaign strategy and then execute: personalized sequences, multi-channel follow-ups, and disciplined pipeline building.

• You can hold a technical conversation with an AI/ML engineer about GPU infrastructure, cloud compute, or distributed training. You don't need to come in as a subject matter expert, but you'll need to learn fast. The buyers you're selling to will know immediately if you can't keep up.

• You're AI-native or close to it. You've already compressed workflows that used to take hours into minutes using AI tools. Research, outreach, call prep, deal tracking. If you're still doing all of that manually, this isn't the right fit.

• You've worked at an early-stage company before, or you're ready to leave the structure behind. There's no sales ops team, no enablement, no SDR layer. You build what you need.

• On-site in San Francisco. We believe the fastest way to build from zero is together, in the room. Expect minimum 60 hours per week.

• Bonus: You have an existing network in the AI/ML or GPU compute ecosystem. You've sold to AI/ML engineers, research labs, academic institutions, or infrastructure buyers before.

The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance.

• Base Salary : $130,000 ~ $ 150,000 per year

• OTE Range : $220,000 ~ $250,000 per year (includes base + commission)

• Perks

  • Medical, dental, and vision insurance

  • Basic Life and AD&D insurance

  • 401(k) retirement Savings plan

  • Unlimited Vacation

Application Review → Initial Screen → Hiring Manager Screen → Take-home Assignment → Deep-dive interview → Leadership Interview → CEO Interview → Offer