Staff AI Engineer | US | 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. The role involves architecting and implementing AI solutions using BigQuery and integrating various HR platforms to unlock insights from People data, improve operational efficiency, and ensure responsible AI practices. Key responsibilities include designing AI workflows, agents, and analytics tools, establishing prompt engineering standards, and setting technical direction for AI architecture within the People technology domain.

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, agents, and analytics tools
  • integrating HR platforms (Workday, Greenhouse, Docebo, Tangelo, Salesforce)
  • BigQuery
  • CI/CD pipelines
  • testing frameworks
  • observability standards for AI systems
  • prompt engineering
  • version control
  • evaluation frameworks for LLM-based systems
  • data governance
  • data privacy
  • responsible AI practices
  • anonymization
  • secure handling of sensitive data
  • access controls
  • AI model governance
  • automation workflow governance
  • security compliance
  • privacy compliance
  • regulatory compliance
  • monitoring and evaluation frameworks for AI systems
  • collaboration with Data Engineering and People teams
  • documentation of systems and architecture decisions
  • AI experimentation
  • AI deployment
  • measurement of impact
  • guidance and enablement to People teams
  • training materials and playbooks for AI-assisted workflows
  • technical leadership

Nice to have

  • experience with Grafana
  • experience with Grafana Mimir, Loki, Tempo
  • experience with open-source projects

What the JD emphasized

  • AI-powered systems
  • intelligent workflows
  • AI-driven solutions
  • AI-powered workflows, agents, and analytics tools
  • LLM-based systems
  • AI assistants
  • AI-driven tools and workflows
  • AI architecture
  • responsible AI practices
  • data governance, privacy, and responsible AI practices
  • anonymization, ethical AI usage, and secure handling of sensitive People data
  • governance standards for AI models, prompts, and automation workflows
  • compliance with internal security, privacy, and regulatory requirements
  • monitoring and evaluation frameworks that ensure AI systems operate accurately, fairly, and reliably over time

Other signals

  • AI-powered systems
  • intelligent workflows
  • AI-driven solutions
  • AI-powered workflows, agents, and analytics tools
  • LLM-based systems
  • AI assistants
  • AI-driven tools and workflows
  • AI architecture