Lead AI/Data Engineer
Dutch, a veterinary telemedicine company, seeks a hands-on Lead AI/Data Engineer in Vancouver to design and operate production AI agents and services while owning AI infrastructure (evaluations, prompt optimization, observability, cost management) and building data pipelines with Snowflake, dbt, Prefect, and event tracking via Segment/Amplitude.
- Compensation
- CA$185K–CA$220K / yr
- Location
- Vancouver
- Work setup
- Hybrid
- Seniority
- Lead
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 6+ years of experience in software, data, or ML engineering
- 2+ years building and operating LLM applications in production
- Strong Python and SQL skills with experience building reliable, maintainable production systems
- Hands-on experience developing AI agents and applications using LLM APIs, agent frameworks, tool calling, retrieval, and structured outputs
- Experience designing and running LLM evaluations, including test datasets, automated graders, regression testing, and systematic experimentation
- Experience with LLM observability, performance optimization, and cost management in production
- Experience deploying and operating services on AWS, GCP, or Azure using containers and CI/CD pipelines
- Working knowledge of modern data platforms, including Snowflake or similar warehouses, dbt, and orchestration tools such as Prefect, Airflow, or Dagster
- Familiarity with product analytics and event tracking platforms such as Segment and Amplitude, or a willingness to learn
- Familiarity with BI tools such as Sigma, Looker, or Tableau
- Comfortable working across AI and data engineering, thriving in a small team with limited direction
Nice to have
- Experience with prompt optimization, semantic layers, data contracts, or A/B testing and experimentation infrastructure
Full description
About Us
Dutch 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.
The Role
We're looking for a hands-on Lead AI/Data Engineer to build and scale the AI systems powering Dutch. You'll
design and ship production AI agents and services for pet parents, veterinarians, and internal teams. You'll also
own the underlying AI infrastructure, including evaluation frameworks, prompt optimization, observability, and
cost management.
You'll help shape our technical approach to AI development, establish engineering standards, and work closely
with product and engineering teams to bring new capabilities into production. This role also includes ownership of key parts of our data platform. You'll build and maintain data pipelines, warehouse models, and analytics and experimentation infrastructure that support our AI systems and broader business needs.
WHAT YOU'LL DO:
AI Services & Platform Tooling (60%)
- Design, build, and operate production AI agents and services for pet parents, veterinarians, and internal teams, grounded in our data and built with appropriate safeguards.
- Own the AI development infrastructure, including evaluation frameworks, prompt optimization, LLM observability, and cost management.
- Establish engineering standards and reusable patterns for retrieval, tool calling, guardrails, and model selection.
- Design and run systematic experiments across models, prompts, retrieval strategies, and agent architectures. Build evaluation datasets and automated tests to measure quality, safety, performance, and cost, and detect regressions.
- Evolve the semantic layer that enables AI systems to answer questions about our business data accurately.
- Work closely with product engineering to deliver AI capabilities through APIs and integrate them into production applications.