We're building the company which will de-risk the largest infrastructure build-out in history.
When people finance GPU clusters, the datacenters housing them, and the infrastructure powering them, they need "offtake" - meaning someone has signed a contract to lease the cluster for a period of time before its even built.
Financing a GPU cluster is inherently risky, since margins are thin and volumes are huge. Lenders don't want to take on the risk that cluster developers can't repay their loan, and cluster developers really don't want to risk not selling their cluster. As a result, risk is offloaded to the customer using fixed-price long-term contracts.
If you don't mitigate this customer risk, there's a bubble. This isn't SaaS anymore - application layer companies sign multi-year contracts for computer and inference, but sell to customers on monthly subscriptions. If you mess up a purchase, it's game over: a minor shift in your revenue growth rate might mean the difference between profit or bankruptcy. But what if companies could exit their contract by selling it back to the market?
Otherwise, as AI scales, compute only becomes available to folks who can effectively take on that risk. A 2-person startup in a San Francisco Victorian can't realistically sign a 5-year take or pay contract on $100m supercomputers. But they may be able to buy the month of liquidity that someone else sold back.
So that's what we make: a liquid market for GPU offtake.
ABOUT THE TOOLING TEAM
We are a small team focused on making SFCompute engineering faster, more observable, and more reliable. Our work spans data infrastructure, developer experience, pre-production environments, and AI tooling β but the common thread isn't any specific domain. It's that we find the problems nobody else owns and make them solved problems.
Everyone on this team wears many hats. You'll work across the stack, collaborate with all parts of engineering, and regularly take on problems that don't fit neatly into a job description. If you want a narrow scope and a clear ticket queue, this team isn't it. If you want to have a large, legible impact on a small team building serious infrastructure, read on.
THE ROLE
We're looking for an Applied AI Engineer to own how AI works for our engineering team. You'll audit how we use tools like Claude Code, identify where AI assistance breaks down or creates friction, and fix it: by writing better skills, rules, and prompts; by improving the context we give AI about our codebase; by changing the workflows that aren't working.
This is a new kind of role. It requires someone who thinks rigorously about information flow, understands how large language models reason, and cares enough about developer experience to go fix things rather than just document them.
WHAT YOU'LL DO
- Audit how engineers across the team use AI tools today β what works, what doesn't, where time is lost
- Maintain and improve our library of AI skills and rules (the structured context that shapes how AI assists our engineers)
- Write high-quality prompts and workflows that reduce toil on common engineering tasks
- Identify gaps in our codebase documentation and context that cause AI tools to give poor output
- Work directly with engineers to understand their pain points and turn them into systemic improvements
- Stay current on AI tooling and evaluate new capabilities as they emerge
- Define and track metrics for AI workflow quality and adoption
WHAT WE'RE LOOKING FOR
- Deep familiarity with AI coding tools (Claude Code, Cursor, Copilot, or similar), not just as a user but as someone who has thought carefully about why they work or don't
- Strong writing skills. Prompts and documentation are core outputs of this role.
- Engineering background or strong technical fluency. You need to understand the code and workflows you're improving.
- Systems thinker. You look for root causes, not just symptoms.
- You can run without a spec. The first thing you'll do is figure out what the problems actually are, not execute on a list someone else wrote.
- Nice to have: experience with prompt engineering, RAG systems, or developer tooling; familiarity with TypeScript or Rust
WHY THIS ROLE
This is a new role category and we're not going to pretend we have it fully figured out. What we know: our engineers use Claude Code every day, the quality of that experience varies a lot, and nobody owns fixing it. You will. The impact is immediate. Every engineer on a small team feels it when the tools get better or worse. And what you build here (the skills, the rules, the workflows) is a real artifact, not a presentation deck.
BENEFITS
GENEROUS EQUITY GRANT
Team members are offered a competitive salary along with equity in the company
VISA SPONSORSHIPS
Yes, we sponsor visas and work permits
RETIREMENT MATCHING
We match 401(k) plans up to 4%
MEDICAL, DENTAL & VISION
We offer competitive medical, dental, vision insurance for employees and dependents and cover 100% of premiums
TIME OFF
We offer unlimited paid time off as well as 10+ observed holidays
PARENTAL LEAVE
We offer biological, adoptive, and foster parents paid time off to spend quality time with family
DAILY LUNCH
We cover lunch daily for employees
UNLIMITED OFFICE BOOK BUDGET
You can buy as many books for the office as you want
The San Francisco Compute Company is committed to maintaining a workplace free from discrimination and harassment.
We make employment decisions based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, belief, national origin, social or ethical origin, age, physical, mental, or sensory disability, sexual orientation, gender identity or expression, marital status, civil union or domestic partnership status, past or present military service, HIV status, family medical history or genetic information, family or parental status including pregnancy, or any other status protected by law.
We welcome the opportunity to consider qualified applicants with prior arrest or conviction records. Our commitment to diversity includes hiring talented individuals regardless of their criminal history, in accordance with local, state, and federal laws, including San Franciscoβs Fair Chance Ordinance and Californiaβs ban-the-box laws.
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