Senior Data & AI Platform Engineer

Dutch•Vancouver, BC

2d•CA$150,000 - CA$195,000•Hybrid

About The Position

Dutch Vet is transforming veterinary care by making expert treatment accessible anytime, anywhere. Our mission is simple: help every pet live their happiest, healthiest life by connecting pet parents with licensed vets through seamless virtual visits. We’re the only veterinary telemedicine service that can diagnose, prescribe, and ship medications directly to customers in most states. For less than $100 per year, Dutch offers real relief and convenience for pets and their families. Backed by world-class investors including Forerunner Ventures, Eclipse Ventures, and Bling Capital, our team is made-up of successful startup founders (Hims, PlushCare, Nasty Gal) with expertise in scaling enterprises (TripAdvisor, Walmart, BARK). Featured in TechCrunch, Forbes, Wired, and Axios, Dutch is setting the standard for quality, accessibility, and compassion in pet care. Most data teams report on the business. Ours builds with it. We're shipping LLM-generated clinical content, agentic assistants, and recommendation systems behind the tools pet parents actually use. This role is a split between data platform architecture and AI infrastructure. Half your time will go toward scaling our Snowflake environment, building semantic layers, and managing clinical data pipelines. The other half will go toward building the backend runtime systems that safely execute our LLM features in production. This is an individual contributor role with no direct reports, but you will be expected to set the technical standard for the team and mentor the engineers and analysts already here. You will report directly to the VP of Data & AI.

Requirements

6+ years operating production data platforms with hands-on ownership of dbt + cloud-warehouses (Snowflake strongly preferred)
6+ years strong production Python and software-engineering fundamentals (typing, testing, code review, and automated deployment)
A default mindset geared toward systems architecture, API contracts, and failure modes
The instinct to manage cloud spend, warehouse performance, and data quality without being asked
People get better at their jobs working with you

Nice To Haves

You've built backend infrastructure for production LLMs (e.g., observability frameworks, evaluation pipelines, or cost attribution)
You have practical ML engineering experience

Responsibilities

Co-own our dbt + Snowflake platform (700+ models, Prefect, Fivetran)
Isolate warehouse workloads and safeguard model dependencies to catch upstream data failures before they break production features
Build the runtime guardrails for our clinical AI—strict payload validation, confidence thresholds, and fallback routing for LLM applications
Develop shared observability pipelines, prompt evaluation harnesses, and cost-tracking tooling for our LLM stack
Set the technical standard for the team, mentoring engineers on Python code quality, CI/CD workflows, and reliable system design