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.

• 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.

Role Description The University of Maine System is seeking an AI Developer to join the IT Enterprise Services team. The AI Developer plays a key role in advancing the University’s digital modernization and sustainability initiatives. This position leverages artificial intelligence to optimize software architecture, automate code modernization, and enhance the performance, security, and maintainability of enterprise applications. Working across the University’s technology ecosystem, the AI Developer applies AI tools and techniques to refactor legacy systems, reduce technical debt, and ensure the long-term reliability of mission-critical applications that support teaching, research, and public service. Key Responsibilities - AI-Driven Code Modernization: - Use AI-powered analysis and automation tools to identify and remediate technical debt across institutional codebases. - Design and implement AI-enabled refactoring processes to modernize legacy systems and migrate applications to modern architectures. - Automated Testing and Quality Assurance: - Develop and maintain comprehensive AI-assisted testing and verification frameworks to ensure performance, reliability, and security in modernized systems. - Application and API Development: - Design, develop, and maintain APIs and full-stack applications that support enterprise operations and data integration needs. - Continuous Improvement and Collaboration: - Integrate AI tools into CI/CD pipelines for proactive quality assurance. - Collaborate with campus stakeholders to translate institutional needs into technical solutions that enhance efficiency and scalability. Salary The salary range for this position is $75,000 to $85,000, commensurate with the candidate's training, education, and experience. Benefits - 13 paid holidays plus earned vacation and sick time - Health, Dental, and Vision insurance - Short-term disability insurance and employer-paid long-term disability insurance - Employer-paid basic life insurance and supplemental life insurance - Tuition waiver program for employees and their dependents (spouse, domestic partner, and dependent children) - 403(b) retirement plan with 10% employer contribution Work Schedule Monday through Friday, 8:00 AM to 5:00 PM EST, with flexibility available as mutually agreed upon between the supervisor and employee. Location This position is fully remote. Applicants must reside and be authorized to work in the United States. Knowledge, Skills, and Abilities Required: - Software Architecture & Modernization: Expertise in modern software architecture, microservices, design patterns, and advanced refactoring techniques for complex, large-scale, and often poorly documented systems. - AI Developer Tooling: Deep, demonstrable knowledge with AI-powered developer tools for static/dynamic code analysis, automated transformation, and intelligent testing (e.g., tools similar to CodeScene, SonarQube, Refact ai, Qodo). - Automated Testing & Verification: Advanced proficiency in building and maintaining comprehensive automated testing suites (unit, integration, end-to-end) and verification frameworks to validate complex system behavior and ensure functional parity post-refactoring. - Programming Languages & Frameworks: Strong proficiency in at least one modern back-end language (e.g., Java, Node.js, Python) and a corresponding front-end framework (e.g., React, Vue.js), with a solid understanding of web fundamentals (HTML, CSS3). - Analytical & System Thinking: Exceptional analytical and creative problem-solving skills, with the ability to diagnose deeply embedded architectural problems in opaque legacy codebases and devise innovative, AI-driven solutions. - Interpersonal & Communication Skills: Excellent verbal and written communication skills, with the ability to articulate highly complex technical concepts, risks, and strategies to diverse technical and non-technical audiences. Qualifications - A master’s degree in Computer Science, Software Engineering, Information Technology, or a closely related field. An equivalent combination of relevant professional experience and education will be considered. - A minimum of five (5) years of professional experience in AI software development, demonstrating progressive responsibility in designing and building complex web applications. - A minimum of two (2) years of dedicated, hands-on experience applying AI/ML tools and techniques to software development lifecycle challenges, such as automated code analysis, AI-assisted refactoring, or generative testing. - A portfolio of completed projects or a detailed professional history that clearly demonstrates expertise in analyzing, improving, and modernizing complex legacy systems with practical application of AI technologies. Preferred - Professional work experience in a higher education, education technology (EdTech), or research-intensive environment. - Experience with advanced AI techniques or contributing to open-source AI/ML projects. - Familiarity with data privacy and governance regulations relevant to the higher education sector, such as the Family Education Rights and Privacy Act (FERPA). How to Apply Materials must be submitted via “Apply Now” below. You will need to complete an application and upload the following: - A cover letter that describes your experience, interests, and suitability for the position. - A resume/curriculum vitae. Important items to know about the recruitment process: - Applications will be reviewed on an ongoing basis and will remain open until filled. - Incomplete application materials cannot be considered. - Candidates selected to proceed to the final stages of the search process will be requested to provide contact information for references. - The successful applicant is subject to appropriate background screenings. - Applicants must be authorized to work in and reside in the United States. Please Note: We are not able to consider applicants who require Visa sponsorship or OPT extensions now or in the future. Company Description The University of Maine System (the System) is an equal opportunity institution committed to fostering a nondiscriminatory environment and complying with all applicable nondiscrimination laws.

• 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 • 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 • 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 • 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.