Staff AI Engineer, People Technology

Grafana Labs is a remote-first, open-source powerhouse. There are more than 20M users of Grafana, the open source visualization tool, around the globe, monitoring everything from beehives to climate change in the Alps. The instantly recognizable dashboards have been spotted everywhere from a NASA launch and Minecraft HQ to Wimbledon and the Tour de France. Grafana Labs also helps more than 3,000 companies -- including Bloomberg, JPMorgan Chase, and eBay -- manage their observability strategies with the Grafana LGTM Stack, which can be run fully managed with Grafana Cloud or self-managed with the Grafana Enterprise Stack, both featuring scalable metrics (Grafana Mimir), logs (Grafana Loki), and traces (Grafana Tempo). We're scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that's okay. If this role excites you, we'd love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity and we are looking for candidates from Canada. Residents of Quebec are not eligible for this role. The Opportunity Grafana Labs is looking for a Staff AI Engineer, People Technology to help build the next generation of AI-powered systems that support our global workforce and People programs. This role sits within the People Technology team, partnering closely with People Operations, Talent Acquisition, Enablement, Finance, and Go-to-Market teams to design intelligent workflows and data products that improve how we hire, develop, and support Grafanistas worldwide. At Grafana Labs, we believe AI should be actually useful. Our approach to AI is grounded in solving real problems and creating practical tools that help teams work better. As part of this philosophy, you'll apply AI thoughtfully within our People systems, building solutions that improve how we operate and support team members. As our first People Team AI Engineer, you'll architect and implement AI-driven solutions that unlock insights from our People data ecosystem, including BigQuery and systems such as Workday, Greenhouse, Docebo, Tangelo, and Salesforce. Your work will focus on creating scalable data pipelines, automation, and AI-powered workflows that drive operational efficiency and deliver actionable insights for People leaders. This role requires both technical depth and a strong understanding of data governance, privacy, and responsible AI practices. You'll help establish standards for anonymization, ethical AI usage, and secure handling of sensitive People data while building systems that empower the People team to make data-informed decisions. As a Staff-level engineer, you will also set technical direction, mentor other engineers, and influence how AI is adopted and governed across the broader organization, not just within the People team. This is an opportunity to play a foundational role in shaping how AI supports the employee lifecycle at Grafana Labs, from recruiting and onboarding to development, engagement, and workforce planning. What You'll Be Doing AI Architecture & People Data Intelligence • 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 • Architect solutions that leverage BigQuery as the central data layer, integrating platforms such as Workday, Greenhouse, Docebo, Tangelo, Salesforce, and other internal systems • Establish and maintain CI/CD pipelines, testing frameworks, and observability standards for AI systems and automated workflows • Define prompt engineering standards, version control practices, and evaluation frameworks for LLM-based systems operating on People data • Partner with People Analytics to ensure AI systems operate on well-governed, high-quality datasets and align with established workforce metrics and data models • Build internal dashboards, AI assistants, or automated workflows that support reporting, insights, and operational efficiency • Collaborate with People partners to translate business problems into scalable technical solutions • Define and track success metrics and measurable business outcomes for AI initiatives, including efficiency gains, time savings, and decision quality improvements Responsible AI, Security & Data Governance • Design systems that securely handle sensitive employee data using anonymization, aggregation, and robust access controls • Establish governance standards for AI models, prompts, and automation workflows, ensuring compliance with internal security, privacy, and regulatory requirements • Implement monitoring and evaluation frameworks that ensure AI systems operate accurately, fairly, and reliably over time Cross-Functional Collaboration & Enablement • Par