VP of Sales

Helios Cloud, Inc.; San Francisco (CA); On-site; USD 180,000 - 380,000; Full time

Benefits offered by this job

Founding-team equity

Uncapped commission

Competitive base salary

Job summary

Helios Cloud, Inc. in San Francisco seeks a VP of Sales to own the entire go-to-market function for GPU cloud, data center capacity, and long-term commitments.

You'll recruit and coach a small team, design the comp plan, and build a repeatable sales engine that scales from first touch to signed contracts. Deep tech fluency in GPUs, power, and networking is essential, as is experience selling multi-year, multi-thousand‑GPU deals.

Qualifications

• Must close complex, high-value B2B infra or technical deals with long cycles.
• Built or shaped a sales system: pipeline, process, forecasting, comp.
• Genuine technical fluency in GPUs, power, and networking; credible with infra leads.

Responsibilities

• Own revenue: close large GPU-capacity commitments and anchor our book.
• Build and lead a repeatable GTM motion; scale AE and sales engineering.
• Define terms, pricing, and contract structures with CEO and finance.

Skills

High-value B2B deals

Sales system design

GPUs/power/networking fluency

Strategic negotiation

People leadership

SF relocation willingness

Job description

Helios takes AI infrastructure A to Z. We secure the power, acquire the land, and build the data center infrastructure, then either colocate customer hardware or operate the cluster ourselves as a neocloud, selling GPU-as-a-Service at well below hyperscaler pricing. Power is the scarcest input in AI infrastructure, so we solve for it first and build everything else around it.

We closed a seed round led by AlleyCorp, are signing $100M+/year in customer revenue, and are scaling globally. We're hiring our first GTM leader, reporting directly to the CEO. You'd own revenue: not just closing deals, but building the machine that generates them.

Why this matters

We're optimists about what AI will do: drug discovery in months instead of years, small teams with the leverage of large ones, work that gets augmented long before it gets replaced.

But the buildout has a cost, and today it lands on whoever lives nearest the site. Conventional data centers strain already-tight grids, demand expansions that take years, and consume millions of gallons of water annually in regions that can't spare it. That's the version of this buildout that turns communities against AI entirely.

Helios is the counter-argument. We deploy at the point of generation, so energy producers monetize excess capacity and the grid absorbs no new strain. We cool closed-loop, with no evaporative water consumption. And we build modular, so capacity arrives in months instead of half a decade. Enabling the buildout and not degrading the places it happens are not in tension. That's the entire thesis, and it's what you'd be selling.

The role

Three things at once:

• A closer who personally carries large, technical, $100M+ deals.
• A builder who stands up a repeatable sales system rather than selling on charisma.
• A technical partner who can sit across from a customer's infrastructure lead and scope the cluster they actually need.

Who you'll sell to

Our customers are AI companies buying committed GPU capacity, often multi-thousand-GPU, multi-year commitments. Selling to them means real fluency in GPUs, power, and networking, and translating a training or inference workload into the right cluster spec. You'll do that yourself at first, then build the sales engineering motion and the AE team that scales it. This is a player-coach seat; at our stage you can't be a pure manager.

You'll have license to build your team from day one. This isn't a "prove it solo for a year, then we'll discuss headcount" seat. If you can make the case for a hire, you make it immediately.

What you'll own

• Revenue. Personally carry and close the large committed GPU-capacity deals that anchor our book.
• Technical selling. Scope clusters with customers' infrastructure and ML leads (GPU type, count, term, networking, storage) and map them to our rate card and available capacity.
• Commercial terms. Contract structure, upfront, term length, and pricing, in partnership with the CEO and finance.
• The sales system. Pipeline stages, qualification criteria, CRM discipline, forecasting: the repeatable motion from first touch to signature, so revenue doesn't live only in your head.
• The sales engineering motion. Turn a workload conversation into a configured, quotable cluster, repeatably, for AEs who aren't as technical as you.
• Top of funnel. Outbound, partnerships, channel, and inbound built into a system that produces qualified opportunities predictably.
• AI-native GTM. Build AI tooling and automation into the sales motion (research, outbound, qualification, proposals, pipeline hygiene) so a small team sells like a large one. Our software team is available to build what you need.
• The team. Hire and develop AEs and sales engineers from day one; set the culture and standards; design the comp plan and the metrics that tell you whether the machine is working.
• The loop with delivery. Partner with hardware and software so what you sell is deliverable on the timelines you commit to, and carry customer signal back into product, pricing, and capacity planning.

How we work

Our culture mirrors our infrastructure: decentralized and built for speed.

• Win-win infrastructure. Our success is tied to the energy producer's monetization and the AI company's latency and cost. If they don't thrive, we don't exist. That shapes how we sell: deals where both sides of the table get something they couldn't get alone.
• Own the outcome. No passengers, only drivers. When you see a gap, you fill it. Anyone can claim an unowned problem off our public gap board, regardless of title.
• Reduce decision latency. The greatest risk is moving too slowly. If a call is reversible and you're 70% confident, make it. Tools and parts under $500 need no approval.
• Build, break, iterate. A good solution shipped today beats a perfect one shipped next month. Every Friday we demo what actually shipped; if it isn't demo-able, it isn't shipped. Post-mortems are blameless and aimed at the process, never the person.
• Scrappy solves. Every constraint has a deployable workaround if you're creative enough to find it. That conviction is why the company exists. Everyone else decided to wait for the grid.
• For this role it means you won't need permission to restructure the pipeline, change how we run pricing conversations, or make a hire. You'll be expected not to ask.

Must-haves

• Personally carried and closed complex, high-value B2B infrastructure or technical deals with long cycles and real negotiation.
• Built or substantially shaped a sales system: pipeline, process, forecasting, comp. You can show the machine you built, not only the deals you won.
• Genuine technical fluency in GPUs, power, and networking. Credible with a customer's infrastructure lead without handing off. We weight this heavily; we'd rather hire someone technically sharp and plainspoken than someone polished who can't hold the technical conversation.
• Substance over charm with both a CTO and a CFO. Clear, precise, and credible in writing and in the room.
• Player-coach: still closing and still configuring while building a team.
• Comfortable owning a number in a business where capacity, pipeline, and product are all still being built.
• Based in, or willing to relocate to, Salt Lake City or San Francisco.
• Sold GPU cloud, compute, data center capacity, power, or comparable infrastructure.
• Background at a neocloud, GPU cloud, hyperscaler, colo/data center, or infrastructure/OEM sales org.
• Sales engineering or solutions architecture background, or a technical degree paired with a sales career.
• Experience with committed-capacity or long-term contract structures.
• Existing relationships with AI companies and infrastructure buyers.

Why Helios

A founding GTM seat reporting to the CEO, with a differentiated product already selling and signed customer revenue, not a slide deck. You own the whole GTM function end to end instead of running one slice of someone else's sales org. Uncapped upside plus meaningful founding-team equity. And a scarce, durable problem: power-constrained AI compute is one of the defining infrastructure bottlenecks of the decade.

Compensation

Competitive base + uncapped commission/variable + meaningful founding-team equity. Level flexes by candidate: VP for a proven GTM leader, or Head of Sales / Founding AE for a strong operator ready to build the function and grow into it.