• Develop and maintain high-quality Python code using Python and its API frameworks • Design and implement Restful APIs that serve Generative AI modules to third parties • Optimize flows and actions manageable through LLM powered agents • Lead and contribute to product development, following SOLID principles and software design patterns to ensure maintainability and scalability • Conduct code reviews and mentor junior developers, promoting high standards of code quality and teamwork • Engage in technical discussions on system architecture, design improvements, and feature implementations • Stay updated with emerging trends in Python, scientific computing, and performance optimization, and sharing insights with the team

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 the U.S. 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 - 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 Bonus Points - Experience working with HR technology ecosystems such as Workday, Greenhouse, and learning platforms - Background in People Analytics or workforce analytics platforms - Experience building internal AI tools, copilots, or automation agents for business teams - Familiarity with workflow automation platforms (Zenphi, n8n, Workato, Zapier, Make, etc.) - Experience working in high-growth SaaS or distributed organizations - Contributions to AI governance frameworks, responsible AI standards, or open-source AI tooling In the United States, the base compensation range for this role is USD $174,986 - USD $209,983. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: - 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. - Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. - Transparent Communication – Expect open decision-making and regular company-wide updates. - Innovation-Driven – Autonomy and support to ship great work and try new things. - Open Source Roots – Built on community-driven values that shape how we work. - Empowered Teams – High trust, low ego culture that values outcomes over optics. - Career Growth Pathways – Defined opportunities to grow and develop your career. - Approachable Leadership – Transparent execs who are involved, visible, and human. - Passionate People – Join a team of smart, supportive folks who care deeply about what they do. - In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. - Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: We will recruit, train, compensate and promote regardless of race, religion, color, national origin, gender, disability, age, veteran status, and all the other fascinating characteristics that make us different and unique. We believe that equality and diversity builds a strong organization and we’re working hard to make sure that’s the foundation of our organization as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy.

• Define and lead the enterprise AI architecture strategy • Design and maintain reference architectures • Provide architectural leadership for AI platforms built on AWS • Lead the evaluation, selection, and integration of large language models • Partner with business, product, and technology leaders to design AI use cases • Establish and enforce AI governance frameworks • Define and oversee AI cybersecurity architecture • Provide architectural guidance for AI-enabled applications • Enable AI lifecycle management practices • Collaborate with cross-functional teams to align AI solutions with standards

• Collaborate with product managers and other stakeholders to understand business requirements and develop data-driven solutions. • Work with operations and product teams to create and improve datasets from human experts. • Setup machine learning tools and manage data pipelines. • Develop AI solutions iteratively with evaluations to automate tasks, make predictions, and optimize processes. • Deploy and monitor AI systems in production, and ensure that they are performing as expected. • Stay up-to-date on the latest trends and developments in data science and machine learning.