VP of Sales

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 Alley Corp, 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.

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.

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.

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.

• 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…