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Grafana Labs

Staff AI Engineer | US | Remote

AI in this role

Build multi-agent AI systems, LLM integrations, and automation infrastructure powering marketing operations at Grafana Labs.

openaiclaudeanthropicgeminicopilotlangchaincrewaipineconeweaviateqdrantchromapgvector+9
prompt-engineeringragllm-integrationai-agentsai-evaluationmulti-agent-systemsbackend-developmentautomation

Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X.

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 seeking a Staff Engineer (AI & Automation) to own the AI agent infrastructure and automation platform that powers our Marketing Operations organization. You’ll build multi-agent architectures, LLM integrations, and backend services that connect AI models to internal and third-party data platforms. You’ll ship production systems that teams depend on daily.

This is a high-autonomy role where you own the technical direction. You’ll identify the highest-leverage problems across Marketing, RevOps, and SDR teams, design the solutions, and ship them. You’ll define the technical direction for the automation platform (data models, API contracts, shared libraries, reference architectures) and partner with Data Engineering, GTM Systems, and Field Operations to build scalable, self-service automation that eliminates manual work and drives operational efficiency.

What You'll Be Doing

Agentic Systems & AI Infrastructure

  • Own end-to-end development of multi-agent AI systems, from architecture and implementation through testing, deployment, and ongoing operation
  • Build modular, composable agentic systems using orchestration frameworks (LangChain, CrewAI, Anthropic MCP, or similar) that operate 24/7 across teams
  • Develop reusable agentic skills that agents invoke across interfaces (Slack, dashboards, internal apps, CLIs)
  • Implement observability and feedback loops including logging, performance metrics, prompt iteration, model evaluation, and cost management
  • Establish governance and compliance standards for AI workflows including access controls, audit trails, PII handling, and human-in-the-loop escalation paths

Systems Integration & Backend Services

  • Build MCP servers, APIs, CLIs, and microservices connecting AI models to business systems (BigQuery, Slack, CRMs, email, calendars, analytics tools)
  • Architect data flows for retrieval-augmented generation (RAG), connecting LLMs to internal knowledge bases, customer data, and real-time business context
  • Build serverless or containerized services (GCP Cloud Functions, Cloud Run) that scale with usage and integrate with Grafana's cloud infrastructure

Automation & Workflow Enablement

  • Partner with RevOps, Demand Generation, Regional Marketing, and SDR teams to scope high-impact automation problems, identify bottlenecks, and build solutions with measurable business outcomes
  • Design and deploy workflows using orchestration tools (n8n, Workato, or custom platforms) with CI/CD, testing, and production reliability standards
  • Build systems designed for self-service with documentation, playbooks, and enablement materials that let partner teams operate independently

We invest heavily in developer productivity. You'll have access to AI coding assistants (Claude Code, Gemini CLI, OpenAI Codex, and others of your choice within security guidelines). We encourage pragmatic AI-assisted development paired with strong code review and quality standards.

What Makes You a Great Fit

  • 8+ years of software engineering experience with depth in backend development, systems integration, or data/analytics engineering
  • 2+ years hands-on experience applying LLMs/AI to production workflows, not just prototypes
  • Strong proficiency in Python and JavaScript/Node.js with Git-based workflows, code review practices, and testing discipline
  • Hands-on experience with LLM frameworks and patterns including prompt engineering, RAG, function calling/tool use, structured output parsing, and evaluation
  • Experience building and operating multi-agent systems at scale including agent decomposition, orchestration patterns (sequential chains, router/dispatcher, parallel fan-out), state management, and production monitoring
  • You diagnose business problems before writing code. You think in workflows and outcomes, not just functions.
  • Deep familiarity with Google Cloud Platform, BigQuery, and serverless/containerized services (Cloud Functions, Cloud Run)
  • Understanding of LLM failure modes and production mitigations including confidence thresholds, fallback logic, human escalation, and cost/latency management
  • Proven ability to identify high-leverage problems, push back on low-impact requests, and deliver end-to-end with minimal direction
  • Fluent with AI-assisted development tools (GitHub Copilot, Cursor, Claude Code). You use AI to build AI systems
  • Clear technical communicator who can explain complex systems in simple terms to both engineers and business stakeholders

Bonus Points

  • Experience with vector databases or retrieval pipelines (Pinecone, Weaviate, ChromaDB, Qdrant, pgvector)
  • Familiarity with marketing or sales platforms (Salesforce, Customer.io, HubSpot, Marketo, Outreach)
  • Experience with frontend frameworks (React, Slack Block Kit) for building user-facing AI tool interfaces
  • Observability tooling for AI systems (LangSmith, Weights & Biases, custom evaluation frameworks)
  • Experience with workflow orchestration platforms (n8n, Temporal, Prefect, Airflow)
  • Familiarity with Model Context Protocol (MCP) or similar standards for connecting AI systems to data sources
  • Prior work automating marketing, sales, or customer success workflows in a B2B SaaS environment
  • Active in open-source communities. Grafana is built on OSS and we value engineers who share that DNA

In the United States, the base compensation range for this role is USD $154,445 - USD $185,334. 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: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation 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.

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How we rate this

Staff AI Engineer | US | Remote at Grafana Labs rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGLLM IntegrationAI agentsAI EvaluationMulti Agent SystemsBackend DevelopmentAutomation

Also common in AI engineer jobs at this level

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you design a retrieval step so the model answers from real data instead of guessing?
  3. How have you integrated a large language model into a production application?
  4. How do you decide when an AI agent can act on its own versus asking for approval first?
  5. How do you decide that one model's output is better than another's for a given task?

Adapt your resume

  • List these exact terms on your resume: Prompt engineering, RAG, LLM Integration, AI agents, and AI Evaluation. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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