Artificial Intelligence Engineer

Do you have experience building your own AI orchestration layer, or just understand in depth how one works under the hood? Strong in Typescript? Happy working within the Bay Area? If so, read on

A well-funded (top-tier VC backed), founder-led security startup is building autonomous agents systems in the vulnerability management space, outpacing traditional firms stuck on legacy tooling 15+ years old. Fresh off the back of strong early growth, they're now looking for software/AI engineers to join the team and contribute to their core product.

Their stack isn't comprised of LangChain/agentic frameworks — their core harness, sandboxed environments, execution engine (the lot) is all built from the ground up in house (Typescript).

The product is already live with large enterprise customers, already surfacing and confirming real-world vulnerabilities within half an hour of public disclosure (traditional firms take 24-72 hours with a much narrower coverage)

Fancy joining and being at the forefront of innovation in this space? Then you'll need

• 3+ years of production engineering experience
• Genuine production experience with AI agents — whether built from scratch or on top of frameworks (LangChain, LangGraph, etc.), provided you can speak to what's happening under the hood. Multi-step reasoning, tool use, memory, evaluation, handling failure gracefully ((If you build agents with frameworks you should know to a high level concepts such as context/trace compaction, how and where traces get stored etc)).
• Solid grounding in distributed systems, with exposure to the harder edges: coordination under failure, safe retries, avoiding duplicate side effects, containing the impact of things going wrong
• Hands-on production experience with a major cloud provider
• TypeScript as your main day-to-day language (or at least 3 years backend exposure with)
• Already working with tools like Claude Code, Codex, or Cursor day-to-day

This is a really unique opportunity to work on that orchestration layer at the deepest level.You'd shape how the system scales, how agents are monitored and debugged once live, and how failure is contained as usage grows.

$200–$300K base + equity.