Senior / Staff Backend Engineer
W3 Global Sourcing · San Francisco, CA
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Jul 14, 2026
San Francisco, CA
Jul 20, 2026
What this job asks for AI summary
A recruiter is pooling backend engineers for multiple AI-focused and data-intensive startups. Day-to-day work covers designing and maintaining backend services, APIs, data models, and async workflows, with full ownership from architecture through deployment and incident response. The role suits experienced engineers comfortable operating cloud infrastructure, diagnosing reliability issues, and guiding technical decisions across fast-growing products.
Senior level · National
“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
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $138,970 (middle half $107,524–$175,762).
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)
This is a pooled/pipeline posting from recruiter w3sourcing.com on behalf of undisclosed AI-native and data-intensive startups — the actual employer(s), specific role details, and work location will only be revealed to candidates who pass a recruiter screen. Location and remote eligibility are therefore genuinely unknown; defaults have been applied.
No compensation figures are provided.
The required backend language is stated as 'Python, Go, Java, Rust, Node.js or similar' — Python is listed as the primary with the others captured as alternatives, reflecting that any one of these satisfies the gate.
'Substantial production backend engineering experience' and ownership of complex projects with limited oversight signal a Senior-level role, though no explicit seniority label or year count appears in the posting.
Infrastructure-as-code is listed under the preferred section without a specific tool named; Terraform is used as the canonical representative.
AI/ML platform and LLM infrastructure experience are listed under 'Preferred but not essential'; LLMs is used as the canonical skill name covering that cluster.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): workflow orchestration.
Read the full posting
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