Staff AI Engineer | Canada | Remote

Grafana Labs Grafana Labs · Data AI · Canada, United States · Remote · People

Staff AI Engineer focused on building AI-powered systems and intelligent workflows for the People Technology team, leveraging sensitive employee data to improve hiring, development, and support processes. The role involves architecting solutions, establishing data pipelines, automation, and AI-driven workflows, with a strong emphasis on data governance, privacy, and responsible AI practices. The engineer will also set technical direction and mentor others.

What you'd actually do

  1. Design and build AI-powered workflows, agents, and analytics tools that transform People data into actionable insights and reduce manual processes across the People Team
  2. Architect solutions that leverage BigQuery as the central data layer, integrating platforms such as Workday, Greenhouse, Docebo, Tangelo, Salesforce, and other internal systems
  3. Establish and maintain CI/CD pipelines, testing frameworks, and observability standards for AI systems and automated workflows
  4. Define prompt engineering standards, version control practices, and evaluation frameworks for LLM-based systems operating on People data
  5. Partner with People Analytics to ensure AI systems operate on well-governed, high-quality datasets and align with established workforce metrics and data models

Skills

Required

  • AI architecture
  • building AI-powered workflows and agents
  • data pipelines
  • automation
  • AI-driven workflows
  • data governance
  • privacy
  • responsible AI practices
  • BigQuery
  • Workday
  • Greenhouse
  • Docebo
  • Tangelo
  • Salesforce
  • CI/CD pipelines
  • testing frameworks
  • observability standards
  • prompt engineering
  • version control
  • evaluation frameworks for LLM-based systems
  • anonymization
  • aggregation
  • access controls
  • monitoring and evaluation frameworks
  • technical leadership
  • mentoring engineers

Nice to have

  • People Operations
  • Talent Acquisition
  • Enablement
  • Finance
  • Go-to-Market teams
  • People Analytics
  • workforce metrics
  • data models
  • internal dashboards
  • AI assistants
  • reporting
  • insights
  • operational efficiency
  • business problems
  • scalable technical solutions
  • success metrics
  • measurable business outcomes
  • efficiency gains
  • time savings
  • decision quality improvements
  • internal security
  • regulatory requirements
  • fairly
  • reliably
  • Data Engineering
  • IT
  • Security
  • Privacy
  • GTM Operations
  • company-wide AI standards
  • architecture decisions
  • governance frameworks
  • AI experimentation
  • deployment
  • measurement of impact
  • AI experimentation
  • deployment
  • measurement of impact
  • training materials
  • playbooks
  • scalable frameworks
  • AI-assisted workflows

What the JD emphasized

  • AI-powered workflows
  • agents
  • data products
  • intelligent workflows
  • AI-driven solutions
  • AI assistants
  • LLM-based systems
  • sensitive employee data
  • data governance
  • privacy
  • responsible AI practices
  • anonymization
  • ethical AI usage
  • secure handling of sensitive People data
  • prompt engineering standards
  • evaluation frameworks for LLM-based systems

Other signals

  • AI-powered workflows
  • agents
  • data products
  • intelligent workflows
  • AI-driven solutions
  • AI assistants
  • LLM-based systems