Imagine a future where every company owns its intelligence.

The AI behind your product is your model, trained on your traffic, tuned to your customers, running at a fraction of today's cost, improving every day from data only you have. Every meaningful company in that future has this. Metergraph gets them there.

That future starts with an urgent problem. AI-native companies now spend a real share of their margins on LLM inference - tens to hundreds of thousands of dollars a month, growing ~7x a year even as per-token prices fall. There are savings on the table - model swaps, caching, batching, context tuning - and almost nobody ships them. Why? Because fine-tuning your system is a lower priority than new feature work, and the models are changing so fast that you’d have to revisit it constantly.

Metergraph solves that. We capture a company's production LLM traffic, connect every dollar to the feature that spent it, and auto-generate evals from their own traffic that prove an optimization is safe before it ships - and stay fresh as models and traffic drift. In early engagements we've validated up to 80% cost reductions on individual AI features, sometimes with quality improving. And every trace and eval Metergraph accumulates is a step toward the opening vision: the corpus that trains company-specific custom models, so every company owns its intelligence instead of renting it.

The company is live with an SDK capturing production spend across multiple applications. We have signed design partners, including companies with six-figure monthly AI spend, and a strong pipeline of leads. We have a technical cofounder - an experienced head of engineering from the AI agent ecosystem - leading development. We now need the founder who can turn pull into a category-defining company.

The Role

This is not a job. It's founding a company with the cold-start problem already solved: validated demand, working product, design partners, a studio behind you, and a path to seed.

You'll own the commercial engine and the company. You'll close early customers through founder-led sales, convert design partners into references, sharpen positioning in a market moving at model-release speed, raise the seed round, and recruit the early team. PSL will be your cofounder and recruiting engine, but the company will be yours to run.

Roles and Responsibilities

• Own founder-led sales end to end: prospect, pitch, close, and expand the first cohort of paying customers among CTOs and engineering leaders at AI-native companies
• Convert live design partnerships into referenceable, paying accounts - and feed what you learn in every deal back into product with your technical cofounder
• Build the GTM machine: pricing and packaging, self-serve motion, content and demand gen aimed at technical buyers
• Raise the seed round on the strength of your storytelling and the traction you created
• Recruit and lead the early team; set the culture, the pace, and the bar

In this role, a typical day might include the following...

• A discovery call with a CTO whose inference bill just crossed $1M/month
• Working a compliance-driven deal where the buying trigger isn't cost, but "which models can we safely use?"
• Whiteboarding with your cofounder on what the eval dashboard has to show before a buyer will act on it without re-checking the work by hand
• Turning a design partner's 50% savings finding into a case study, a blog post, and four warm intros
• Testing the seed narrative on a friendly investor, then rewriting the two slides that didn't land
• Deciding, with imperfect information, what the company will not do this quarter

Signs this might be a fit

• You've sold infrastructure, devtools, observability, or cost-optimization products to technical buyers - and you know that selling savings to engineers is really selling trust
• You've done founder-led sales, or you were the first commercial hire who built the machine from nothing
• You've founded a company before - or you've been thinking about it
• You can hold your own in a technical conversation about models, evals, and inference economics - engineers trust you within ten minutes
• You think "do more for less" is a capability story, not a discount story

Preferred Skills and Qualifications

• 7+ years in commercial leadership at infrastructure, devtools, or SaaS companies selling to technical buyers
• A track record of closing deals personally - not just managing a team that did
• Comfort with ambiguity, risk, and the emotional range of zero-to-one
• Low-ego partnership style; you want a strong technical cofounder, not a staff
• Fluency (or fast-developing fluency) in the LLM ecosystem: providers, pricing, evals, deployment constraints
• Based in or willing to be regularly present in Seattle