
Founding SWE / MLE
San Francisco, NY at a glance
- Rent
- #3 of 51$2,680/mo+44% vs US avg
- Weather
- #21 of 51295 mild days0 hot · 0 cold
- Income tax
- #3 of 5110.9% top rateNew York
What you need
Tech
Experience
- 1+ yrs AI/ML engineering
What you'll do
- Build core enforcement engine
- Deploy Salus in customer codebases
- Research benchmarks and authorization
- Own real surface area
Salus is the runtime enforcement layer for AI agents. We sit between an agent and its tools, intercept every action before it executes, and check it against declarative policy, so agents can take real actions in production without doing the wrong thing. We're YC W26, we’re a group of researchers and engineers trying to combine both to get the best results in a productized manner.
We're looking for a founding engineer who is genuinely cracked across three things most people are only good at one of: LLMs and agents, systems, and shipping real software. You'd be one of our first engineers, working directly with me on everything from the core product to deploying Salus inside customer codebases to the research that keeps us ahead.
What you'd do:
- Build the core enforcement engine, the thing that intercepts tool calls, evaluates policy deterministically, and returns something the agent can actually recover from
- Go into customer codebases and get Salus deployed against real agent stacks (LangChain, LangGraph, MCP, whatever they're running)
- Work on the research side with us, benchmarks, adversarial evaluation, and the harder problems around agent authorization and provenance that our papers come out of
- Own real surface area from day one, this is a founding role, not a ticket queue
What we're looking for:
- Deep with LLMs and agents, you understand tool calling, context, eval, and where agents actually break in production
- Strong systems engineer, low-latency and correctness-critical code doesn't scare you
- Excellent all-around SWE, you go from a vague problem to a working thing fast
- Comfortable straddling product and research, you want to build the thing and figure out the hard open problems behind it
- You move fast, have taste, and want to be early at something that matters
- Honestly, just be cracked at anything. If you’re really good at anything, please apply
Bonus if you've built agent infrastructure, worked on security, verification, or formal methods, deployed into enterprise environments, or have research chops (papers welcome, not required).
This is an in-person role in San Francisco / NYC. We're small, we're moving fast, and the ceiling here is enormous.
Interview Process
Intro Call → Take Home → Final Call → Offer
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About Salus
Your agent processed a refund without looking up the order ID, costing you thousands. You only found out three hours later from a support ticket. Evals, output scoring, and observability can reduce the likelihood of mistakes like these occurring - but there's no solution that inspects and prevents an action as it’s about to execute. Salus does that. We’ve built an API that wraps around your agent and checks its actions at run time, blocking incorrect ones and providing immediate feedback to guide retries. Kevin and Vedant were roommates at Stanford, where they both studied computer science.
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