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Founding SWE / MLE

  • Office
  • 0-3 years

Salary

$250,000 - 500,000/ year

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Description

The company 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 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 the company 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 the company 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

Requirements

  • 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.
  • Experience: 1+ years
  • Visa: Will sponsor

Where you’d work

From the office

You can work from

  • United States

Visa sponsored

About the company

Company hidden

  • Industry: AI

Your chances

Still hiring, already crowded, and a person reads your message.

  • 19 checks run
  • 6 good signs
  • 4 red flags

Still hiring?

12 checks

Actively hiring

In its favour4

  • Still on the company's own careers site, checked 3 h agoModerate evidence
  • Specific about the basics: pay, place, level, stack and contract all statedSlight evidence
  • States its salarySlight evidence
1 moreFewer
  • A hiring contact is attached to itSlight evidence

How crowded?

7 checks

High

Against it4

  • Open for 2 weeks: applications have had time to pile upModerate evidence
  • Entry level: the most applied-to level there isModerate evidence
  • Sponsors visas: applicants from abroad compete for it tooSlight evidence
1 moreFewer
  • Pays more than 99% of similar roles: that draws applicantsSlight evidence

In its favour2

  • You can message the hiring contact and skip the queueModerate evidence
  • Asks for LangChain, which only 1% of open roles doSlight evidence
74 roles like this are in their Early WindowFound before the big job boards, while the crowd hasn’t arrived

Fits Me

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  • Level
  • Stack
  • Work model
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  • Must-haves
Details12 facts · Role, Location, Compensation, Employment, Company
Tech stack
  • Python
  • LLMs
  • LangChain
Type
Full-time
Industry
AI
Specialty
Backend
Region
United States
Pay period
Annual
Show 6 more factsShow less

Role

Category
Development
Specialty
Backend
Experience
1+ years
Tech stack
  • Python
  • LLMs
  • LangChain

Location

Work model
Office
Region
United States
Remote from
  • United States
Visa sponsorship
Sponsored

Compensation

Salary
$250,000 - 500,000 / year
Pay period
Annual

Employment

Type
Full-time

Company

Industry
AI

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