Grafana Labs - Staff AI Engineer, People Technology | Canada | Remote

• 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 • Partner closely with Data Engineering and teams across People, IT, Security and Privacy, Finance, and GTM Operations to align data architecture and AI capabilities • Collaborate with other AI Engineers across the organization to align on architecture patterns, shared tooling, and company-wide AI standards • Document systems, architecture decisions, and governance frameworks for People AI initiatives • Help establish internal standards for AI experimentation, deployment, and measurement of impact • Provide guidance and enablement to People teams adopting AI-driven tools and workflows • Create training materials, playbooks, and scalable frameworks that enable People team members to confidently build, trigger, and measure AI-assisted workflows independently • Technical Leadership • Set technical direction for AI architecture within the People technology ecosystem • Mentor and provide technical guidance to engineers and technical partners working on adjacent systems • Influence cross-functional architecture decisions, advocating for responsible, scalable, and well-governed AI practices across the organization • Drive alignment between AI initiatives and broader engineering standards, ensuring People systems are not built in isolation • What Makes You a Great Fit • 7+ years of engineering or data engineering experience, including 2+ years working with 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 analytics • Proficiency in Python, SQL, modern APIs, and LLM platforms or frameworks (OpenAI, Gemini, Claude, or similar), including integrating enterprise SaaS systems such as HRIS or CRM platforms • Experience designing scalable data pipelines, automation frameworks, and analytics platforms, with a strong knowledge of data modeling, ETL/ELT pipelines, and analytics infrastructure • Experience working with sensitive data environments and implementing responsible AI practices, including anonymization, access controls, governance, and regulatory considerations when applying AI to People data • Ability to partner with both technical and non-technical stakeholders to define and deliver solutions, document systems clearly, and translate evolving business needs into scalable technical solutions