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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and operating AI agents and applications, with a strong focus on LLM development, data pipeline management, and performance optimization. Proficient in Python and SQL, with experience in deploying services on cloud platforms and maintaining data quality and governance.
Highest-signal resume keywords
LLM Application DevelopmentPython ProgrammingSQL ProficiencyData Pipeline ManagementCloud Deployment (AWS, GCP, Azure)
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI Agent DevelopmentLLM Evaluation DesignAutomated TestingData Quality AssuranceEvent TrackingPerformance OptimizationCost ManagementPrompt OptimizationData Mart DevelopmentSystematic Experimentation
Soft Skills
Problem SolvingCollaborationAttention to Detail
Tools & Technologies
SnowflakePrefectFivetranAirbyteSegmentAmplitudeCI/CD PipelinesContainerization
Industry Keywords
AI DevelopmentMachine Learning EngineeringData GovernanceProduct AnalyticsEvent Tracking
Tech Stack
Tools & technologiesAirflowAWSAzureGoogle Cloud PlatformPythonSQLTableau
About the role
Key responsibilities & impact- 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
What you’ll need- 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
Comp & perks- 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!