AI Engineer
Instabase · San Francisco, CA
$230,000–$315,000from the description
Jul 22, 2026
San Francisco, CA
Jul 23, 2026
What this job asks for AI summary
A staff-level engineering role focused on building the core runtime that powers an AI agent platform. The work centers on designing state machines for agent execution, secure sandboxed environments for running untrusted code, tool-calling middleware, and system-level security guardrails. Suited to engineers with deep distributed systems backgrounds and hands-on experience building or operating production LLM orchestration or agent execution frameworks.
Staff level · 8+ years · San Francisco-Oakland-Berkeley, CA · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 75 people in the San Francisco-Oakland-Berkeley, CA area plausibly meet what this posting asks for (software developers). range 45–110
Applicant volume Light — Few people clear these requirements, so an application that does clear them gets looked at. Worth applying to even if you miss a nice-to-have.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $190,744 (middle half $167,095–$224,501). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (6)
The posted salary range appears to contain a typo: '$230,00' is almost certainly $230,000, so the range is interpreted as $230,000–$315,000/year.
The role is listed as #Li-Hybrid, indicating an in-office/hybrid expectation at the San Francisco location; it is not fully remote.
The JD requires a Bachelor's or Master's degree 'or equivalent practical systems engineering experience,' so no hard degree gate is set.
LangChain and AutoGen are listed as examples of agent orchestration frameworks under the required agentic AI expertise section; they are captured as a required skill with alternatives, reflecting that any comparable system satisfies the requirement.
gVisor and WebAssembly appear in the responsibilities narrative as illustrative sandboxing options alongside Docker (which is required); they are marked preferred as they are not explicitly gated in the qualifications section.
The 2-year figure for agentic AI / LLM orchestration experience is stated at the role level ('2+ years of production experience building or modifying agent execution environments'), not tied to a single named tool, so it is attached to the LLMs skill as the closest representative technology.
Read the full posting
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