Staff AI Enablement Engineer at Trustly
San Francisco, CA
$250,000–$315,000
Jul 5, 2026
San Francisco, CA
Jul 21, 2026
What this job asks for AI summary
A senior individual-contributor role focused on building and maintaining internal AI infrastructure — covering LLM integration, prompt management, evaluation pipelines, and agentic workflow tooling — so that teams across the business can adopt AI-powered ways of working. The engineer will also prototype new architectures, set evaluation standards, and create reusable libraries and patterns that help product and engineering teams ship AI capabilities into production systems such as payments, fraud detection, and risk decisioning. Suits an experienced engineer with a strong background in applied LLM systems who is comfortable operating across multiple teams and driving technical decisions independently.
Staff level · 8+ years · Remote · Full-time
Pay in the description: $250,000–$315,000
Posted 2 times — it's one opening, so apply once.
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 7,200 people nationally plausibly meet what this posting asks for (software developers). range 2,150–10,900
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 $138,970 (middle half $107,524–$175,762). 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 role is posted as fully remote across all US locations; the salary range ($250K–$315K/year) reflects base pay only and covers all US geographies.
The 3-year AI/ML focus is stated as a sub-requirement within the overall 8+ years of software engineering experience; it is treated as a hard gate since it appears in the primary requirements block.
RAG, fine-tuning, prompt engineering, function calling, and agentic workflows are all listed together in a single 'deep hands-on experience' sentence in the requirements section. Function calling appears alongside the others but is the least emphasized; it is retained as preferred given the bundled phrasing leaves some ambiguity about individual gates.
Evaluation frameworks and pipelines are described as a core responsibility ('own evaluation standards') but no specific tooling is named, so no named tool skill is emitted — the concept is captured in the responsibilities rather than as a concrete technology.
The alternative occupation code 15-1299 is noted because this role blends platform/infrastructure engineering with applied AI enablement in a way that doesn't map cleanly to a single standard occupation; 15-1252 wins because the primary day-to-day work is building software systems (LLM infrastructure, internal platforms, tooling).
This posting reads as a fully-remote role, so it was scored against the national candidate pool rather than a single metro.
Read the full posting
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