Senior Data Engineer building Azure pipelines, data platforms, and ML workflows for Manulife’s retirement operations. Supporting trusted analytics across North American teams.
About the role
- Lead AI/Data Engineer building production AI agents, data pipelines, and analytics infrastructure. Powering Dutch’s veterinary telemedicine platform for pet parents and veterinarians.
Responsibilities
- Design, build, and operate production AI agents and services for pet parents, veterinarians, and internal teams
- Own 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 enabling AI systems to answer questions about business data accurately
- Work with product engineering to deliver AI capabilities through APIs and integrate them into production applications
- Build and maintain ELT pipelines and dbt models in Snowflake using Prefect, Fivetran, and Airbyte
- Develop trusted data marts and datasets supporting AI features, product analytics, and experimentation
- Build the data foundation for experimentation, including consistent metrics, baselines, and feature-impact measurement
- Maintain automated data quality tests, freshness checks, and alerts for critical pipelines
- Diagnose pipeline failures, address root causes, and improve reliability
- Support warehouse security, governance, performance, and cost management
- Build and maintain event data pipelines from Segment into Amplitude, Iterable, and Snowflake
- Define and validate event tracking plans for new features with product engineering
- Diagnose and resolve identity resolution, user property, and event tracking issues
- Support product experimentation through reliable event tracking and accurate outcome measurement
- Build and maintain Amplitude dashboards and reports to measure user behavior and feature performance
Requirements
- 6+ years of experience in software, data, or ML engineering, including 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
- Bonus: Experience with prompt optimization, semantic layers, data contracts, or A/B testing and experimentation infrastructure
- Love animals
Benefits
- Hybrid working location
- Health, Dental and Vision Insurance
- Life and Disability Insurance
- Flexible PTO
- Robust Holiday Schedule
- Registered Retirement Savings Plan
- Mental Wellbeing Options
- Growth Opportunities!
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