Member of Technical Staff – Applied AI
Hone
San Francisco, CA · Posted October 6, 2026
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November 2026
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Pay compared with the market
This listing does not state pay. Across 130 open member of technical staff listings that state pay, the middle half runs $208,000 to $270,000 and the median is $240,000.
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How AI is used in this kind of work
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Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
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About the job
Hone builds AI that owns outcomes, not tasks: agentic systems that work towards goals over weeks and months, deploy themselves, and improve over time.
ABOUT HONE
Models keep getting smarter, but outside of coding most organizations can't absorb that intelligence, and the gap between model capability and the value derived from it keeps widening. The reasons are many, from human incentives to org design, but at the core we think it's a technology problem. Hone builds engines: AI systems that you hand a goal, like "keep the recruiting pipeline healthy." An engine builds itself, maintains its own agents and code, pulls in people when it needs judgment, and learns from every correction.
In October 2026, we announced a $60M seed round https://hone.com/blog/introducing-engines/ from Benchmark and Index Ventures.
- Half our team are former founders: They’ve built companies, shipped products, and chosen Hone as the place to build next. The rest of us come from Cognition, Mercor, Ramp, Jane Street, Decagon, Brex and Harvey
- Our customers are building with AI themselves: Cognition, Modal and Lucanet already use Hone, with customer perspectives featured on our website https://hone.com/
- Our founders have built from research to scale: They researched agents at Stanford, built the core of Devin at Cognition, led enterprise engineering at Mercor, built internal AI platforms, and founded companies that reached over one million users
- We measure our work by economic impact: Engines are deployed across revenue, procurement, risk, product and operations, and we judge them by the results they create, not benchmark scores
- Our values shape how we work: Own the Outcome, Set the Standard, Win with Class, and Commit to the Racing Line. Read more on our careers page https://hone.com/careers/
- Read more: Bloomberg https://www.bloomberg.com/news/articles/2026-10-08/former-openai-cognition-staffers-want-ai-to-help-run-a-business, Index Ventures’ investment thesis https://www.indexventures.com/perspectives/ai-that-owns-business-outcomes-our-investment-in-hone/, and our launch announcement https://hone.com/blog/introducing-engines/
THE ROLE
Every engine runs inside a customer's systems, with a team accountable for its outcome. You'll own getting engines there: scoping customer goals into engine specs, taking engines live with customer teams, owning a set of accounts with an engineering owner, and building the systems that automate deployment until engines deploy themselves.
WHAT YOU'LL WORK ON
- Discovery with customer teams, scoped into engine specs: objectives, evals, permissions and connectors.
- Taking engines live, initial testing to autonomous operation.
- Operating engines that change their own agents and code after launch: evals, corrections and rollbacks.
- Triage of customer asks into configuration, bounded workarounds and product fixes.
- Automating deployment itself: build out internal systems that automate use case discovery, scoping, and implementation, and over time turn them into first class product primitives.
- Working with the core engineering and product teams to inform upcoming roadmap based on customer feedback and usage.
REQUIREMENTS
- 2+ years of experience in engineering, forward-deployed work or a functional domain, or equivalent depth from research, open source or your own projects
- Time at a fast-growing startup
- A clear spike as an engineer, a forward-deployed engineer, or a functional expert in areas like GTM, finance or operations who builds with AI
- You've built something from scratch and stayed with it in production: a deployment, a product or a function
- Strong technical fundamentals: APIs, auth, data pipelines, enterprise systems, agents
- You turn ambiguous problems into clear specs and know when to cut scope
- You use coding agents regularly and still understand every line you ship
- You build and tinker for fun because you genuinely care about how the technology works
NICE TO HAVE
- Deployment experience at an AI startup or lab
- Experience designing evals
HOW WE HIRE
1. Intro with a co-founder.
2. Technical screen.
3. Deployment case study.
4. One-day onsite in San Francisco.
5. References.
6. Offer.
LOGISTICS
- Location: San Francisco, in person, Sunday to Friday.
- Compensation: Competitive salary + meaningful equity.
- Visa: We sponsor visas and support you through the immigration process.
- Benefits: Health and dental insurance, maternity and parental support, and relocation support.