Staff AI Engineer | US | Remote

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.

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.