Senior Data & AI Platform Engineer
Dutch · Vancouver, WA
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Jul 1, 2026
Vancouver, WA
Jul 21, 2026
What this job asks for AI summary
A senior individual contributor role split between data platform engineering and AI infrastructure. The work involves maintaining and scaling a large dbt/Snowflake environment with clinical data pipelines, while also building the backend runtime systems that power production LLM features — including guardrails, observability tooling, and prompt evaluation. The position also carries an informal technical leadership responsibility, mentoring existing engineers and analysts.
Staff level · 6+ years · National · Full-time
“or” means any one of them counts — you don't need all of them.
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
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 $142,568 (middle half $111,775–$173,013). 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)
This role is based in Vancouver, Canada (hybrid) — compensation is quoted in CAD. US benchmark data will not apply.
The role is a genuine hybrid between data platform architecture (dbt/Snowflake/pipelines) and AI/LLM backend infrastructure, making SOC classification genuinely ambiguous. 15-1243 (Database Architects) was chosen as the primary code because the data platform half is explicitly described first and involves 700+ dbt models, semantic layers, and clinical data pipelines; 15-1252 (Software Developers) is a strong runner-up given the LLM runtime/backend engineering half.
Seniority is assessed as Staff despite no 'Staff' title: the JD explicitly states this IC role is expected to 'set the technical standard for the team' and mentor engineers and analysts, with direct reporting to the VP of Data & AI — scope that exceeds a typical Senior engineer.
Prefect and Fivetran appear in the 'What You'll Do' responsibilities section describing the existing platform the candidate will co-own; they are treated as required context for the role rather than gated skills, but are included as must-have given the explicit co-ownership framing.
LLM observability frameworks, evaluation pipelines, and cost attribution, as well as practical ML engineering experience, are listed under the 'Even better' (nice-to-have) section and are marked preferred accordingly.
The JD mentions 'LLM-generated clinical content, agentic assistants, and recommendation systems' as the AI work context; LLMs is marked required because building runtime guardrails and evaluation harnesses for LLM applications is explicitly listed as a core responsibility ('the other half will go toward building the backend runtime systems that safely execute our LLM features in production').
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): ML engineering.
This role's work location reads as outside the US — the candidate pool, comp, and contention benchmarks here are US-only (BLS employment, Adzuna/USAJOBS demand, and certified H-1B wages), so treat them as a rough US reference, not a local market.
Read the full posting
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