Senior AI Engineer
Weave · CA
$175,000–$215,000from the description
Jul 14, 2026
CA
Jul 21, 2026
What this job asks for AI summary
A senior backend engineering role focused on the AI layer of a drug-development regulatory platform. The work centers on building LLM-facing backend services, designing and validating pipelines such as prompt construction, retrieval systems, and tool-calling workflows, and creating automated evaluation frameworks to measure quality, reliability, and cost in production. A background in machine learning or life sciences is preferred.
Senior level · San Francisco-Oakland-Berkeley, CA · Full-time
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 490 people in the San Francisco-Oakland-Berkeley, CA area plausibly meet what this posting asks for (software developers). range 210–740
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
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 (7)
The role sits at the intersection of backend software engineering and applied AI/LLM work. SOC 15-1252 (Software Developers) was chosen as the primary code because the JD explicitly emphasizes 'production-ready backend code' and shipping LLM-powered products; 15-2051 (Data Scientists) is a credible runner-up given the scientific/quantitative background requirement and emphasis on experimentation and metrics.
No specific programming language is named anywhere in the posting — the JD describes LLM-facing backend work generically without calling out Python, Go, or any other language.
The scientific/quantitative background (ML, statistics, CS, biology, chemistry) is framed as 'What You'll Bring' but reads as a background descriptor rather than a hard gate on a specific named technology; it is captured under preferred skills for machine learning and statistics.
Life-sciences or biotech/pharma domain experience is explicitly marked 'preferred' in the JD.
Early-stage startup experience and regulated-environment software development are listed as 'Bonus' items and are not captured as skills since they name no specific technology or tool.
The role is hybrid (Tues/Wed/Thurs in-office in San Francisco), not fully remote.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): backend development.
Read the full posting
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