Senior Platform Engineer, Applied AI
Recruiting From Scratch · San Francisco, CA
$250,000–$350,000from the description
Jul 20, 2026
San Francisco, CA
Jul 22, 2026
What this job asks for AI summary
A senior infrastructure role at a Series A AI data and evaluation startup, focused on designing and maintaining the shared platform that underpins AI data generation, evaluation pipelines, and distributed compute. Day-to-day work spans Kubernetes-based cloud infrastructure, backend services in Node.js and Python, and distributed systems using Kafka, Redis, and Elasticsearch, with additional responsibility for developer tooling and mentoring engineers. Suited to engineers with 6–10 years of backend or platform infrastructure experience, ideally from high-growth or data infrastructure environments.
Senior level · 6+ 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 770 people in the San Francisco-Oakland-Berkeley, CA area plausibly meet what this posting asks for (software developers). range 570–1,000
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
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 (8)
The role is titled 'Senior Platform Engineer, Applied AI' and is on-site 5 days/week in San Francisco — remote=false.
Compensation is quoted as a base salary range of $250,000–$350,000/year; OTE of $300,000–$450,000 is also mentioned but reflects variable/equity components, so base figures are used for the comp fields.
Node.js and Python appear together under 'Strong backend engineering experience with Node.js and/or Python' in the Technical Requirements section — they are listed as interchangeable alternatives on the same requirement, but both are also called out independently in the 'What You'll Do' section, so both are captured as a paired must-have.
AWS and GCP appear as 'AWS or GCP cloud architecture' in the Technical Requirements section — treated as interchangeable alternatives on a single hard-gated requirement.
Kafka, Redis, and Elasticsearch appear as 'Kafka, Redis, Elasticsearch, or similar distributed technologies' in Technical Requirements — all three are named and captured; Kafka is the primary with Redis and Elasticsearch as alternatives on that specific line, but Redis and Elasticsearch are also emitted as standalone must-haves given their independent mention in the 'What You'll Do' section.
The degree requirement is listed as 'preferred' throughout (Bachelor's preferred, Top-30 CS preferred, exceptional candidates without considered) — no hard degree gate exists, so the degree requirement is set to None.
Experience supporting AI/data infrastructure is explicitly marked 'preferred' in the posting, so it is captured as a preferred skill.
SOC confidence is Medium: the role writes and ships platform infrastructure code (15-1252 Software Developers), but the heavy cloud/Kubernetes/ops framing creates some ambiguity with 15-1244. The primary day-to-day work — building internal developer platforms, backend services, deployment tooling — points to 15-1252.
Read the full posting
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