Staff AI Engineer, People Technology

About the Role

Join Grafana Labs as a Staff AI Engineer, People Technology, to architect and implement next-generation AI-powered systems that support our global workforce and enhance People programs. This is a foundational role to shape how AI drives efficiency and insights across the entire employee lifecycle.

Responsibilities

• Design and build AI-powered workflows, agents, and analytics tools to transform People data into actionable insights and reduce manual processes.
• Architect solutions leveraging BigQuery, integrating with systems like Workday, Greenhouse, Docebo, Tangelo, and Salesforce.
• Establish and maintain CI/CD pipelines, testing frameworks, and observability standards for AI systems.
• Define prompt engineering standards, version control, and evaluation frameworks for LLM-based systems.
• Design systems that securely handle sensitive employee data using anonymization, aggregation, and robust access controls.
• Implement monitoring and evaluation frameworks to ensure AI systems operate accurately, fairly, and reliably.
• Set technical direction for AI architecture within the People technology ecosystem and mentor other engineers.

Requirements

• 7+ years of engineering or data engineering experience, with at least 2 years focused on AI/ML systems or LLM-based workflows.
• Demonstrated ability to set technical direction, mentor engineers, and drive organization-wide impact through AI or automation initiatives.
• Strong experience working with Google Cloud Platform and BigQuery for data processing and analysis.
• Proficiency in designing and implementing scalable data pipelines and automation workflows.
• Experience with data governance, privacy, and responsible AI practices, including anonymization and secure data handling.
• Familiarity with CI/CD practices, testing frameworks, and observability for AI systems.

Nice-to-Haves

• Experience with HRIS systems (e.g., Workday) and recruiting platforms (e.g., Greenhouse).
• Knowledge of prompt engineering best practices and LLM evaluation techniques.
• Experience building internal dashboards or AI assistants for business users.