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 managementYou’ll help shape our technical approach to AI development, establish engineering standards, and work closely with product and engineering teams to bring recent 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 needsDesign, build, and operate production AI agents and services for pet parents, veterinarians, and internal teams, grounded in our data and built with appropriate safeguardsOwn the AI development infrastructure, including evaluation frameworks, prompt optimization, LLM observability, and cost managementEstablish engineering standards and reusable patterns for retrieval, tool calling, guardrails, and model selectionDesign 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 regressionsEvolve the semantic layer that enables AI systems to answer questions about our business data accuratelyWork closely with product engineering to deliver AI capabilities through APIs and integrate them into production applicationsBuild and maintain reliable ELT pipelines and dbt models in Snowflake,



using Prefect for orchestration and Fivetran and Airbyte for data ingestionDevelop trusted data marts and datasets that support AI features, product analytics, and experimentationBuild the data foundation for experimentation, including consistent metrics, baselines, and measurement of feature impactMaintain automated data quality tests, freshness checks, and alerts for critical pipelinesDiagnose pipeline failures, address root causes, and improve reliabilitySupport warehouse security, governance, performance, and cost managementBuild and maintain reliable event data pipelines from Segment into Amplitude, Iterable, and SnowflakePartner with product engineering to define and validate event tracking plans for new features, ensuring accurate and consistent instrumentationDiagnose and resolve identity resolution, user property, and event tracking issues that affect AI systems and product analyticsSupport product experimentation through reliable event tracking, consistent metrics, and accurate measurement of experiment outcomesBuild and maintain Amplitude dashboards and reports that help product teams understand user behavior and measure feature performanceHands-on experience developing AI agents and applications using LLM APIs, agent frameworks, tool calling, retrieval, and structured outputs You use evaluations, experiments, and data to guide decisions and continuously improve system performance You thrive in a small team, set priorities independently, and make progress with limited direction You take ownership of technical decisions,



from architecture and implementation through deployment and ongoing operations Familiarity with BI tools such as Sigma, Looker, or Tableau You work effectively across data, product, and engineering teams, and understand how to integrate AI capabilities into existing applications Experience deploying and operating services on AWS, GCP, or Azure, using containers and CI/CD pipelines Familiarity with product analytics and event tracking platforms such as Segment and Amplitude, or a willingness to learn Experience designing and running LLM evaluations, including test datasets, automated graders, regression testing, and systematic experimentation You’re comfortable working across AI and data engineering, including pipelines, data models, and analytics infrastructure You love animals Working knowledge of modern data platforms, including Snowflake or similar warehouses, dbt, and orchestration tools such as Prefect, Airflow, or Dagster Experience with LLM observability, performance optimization, and cost management in production You build reusable tools, frameworks, and infrastructure that help teams develop and ship AI capabilities faster You’ve built and operated production AI systems that people rely on, and you know when AI is the right solution to a problem Strong Python and SQL skills, with experience building reliable, maintainable production systems You communicate technical decisions clearly and document your work so others can build on it6+ years of experience in software, data, or ML engineering, including 2+ years building and operating LLM applications in production Experience with prompt optimization, semantic layers, data contracts, or A/B testing and experimentation infrastructure#J-18808-Ljbffr

📌 Lead Ai And Data Engineer (Vancouver)
🏢 Dutch
📍 Vancouver