Senior Software Engineer, Grafana Labs

• 5+ years of software engineering experience, including backend development and systems integration work
• Strong proficiency in Python (preferred) or Javascript/Node.js
• Hands-on experience with LLM APIs (OpenAI, Anthropic Claude, or similar) and orchestration libraries (LangChain, LlamaIndex, Anthropic MCP, Semantic Kernel, etc.)
• Comfortable building internal APIs, microservices, or serverless systems (GCP Cloud Functions, Cloud Run, AWS Lambda, or similar)
• Familiarity with SQL and data warehouses (BigQuery preferred)—you understand how to query, structure, and pipeline data for AI workflows
• Experience with authentication patterns, secure API handling, rate limiting, and workflow automation
• Proven ability to deliver AI-powered features in production environments—you've shipped tools that real users depend on
• Strong problem selector who can identify high-leverage initiatives and push back on low-impact requests
• Thrives in ambiguous, fast-moving projects; able to balance experimentation with engineering rigor
• Clear technical communicator—you can explain complex systems in simple terms and collaborate effectively with product and data stakeholders
• Comfort with autonomy—you identify the right questions, structure unstructured problems, and drive work independently
• 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

Desirable

• Grafana's Revenue Operations organization is looking for a Senior Software Engineer focused on building AI-powered internal tools and agentic workflows for our GTM teams
• You'll own the technical infrastructure that powers automation across Sales, Customer Success, and Marketing—from agentic skills that automate SDR outreach to backend services that connect AI models to Salesforce, Slack, BigQuery, and internal data platforms
• You'll be the technical architect behind systems that give every GTM team member leverage
• Part systems builder and part problem detective, you'll identify bottlenecks across the business, design automated solutions using LLM APIs and orchestration frameworks, and ship tools that people actually use
• Your work will directly shape how Grafana's GTM organization scales
• You'll partner closely with Data Engineering, GTM Systems, Field Operations, and GTM leadership to build scalable, self-service automation that reduces manual work and surface intelligence
• Own end-to-end development of agentic and AI-integrated workflows: design, implementation, testing, deployment, and maintenance
• Build modular, composable agentic systems using frameworks like LangChain, CrewAI, Anthropic MCP, or similar orchestration libraries
• Develop "agentic skills" for SDR and CSM teams—reusable capabilities that agents can invoke across interfaces (Slack, dashboards, internal apps)
• Implement observability and feedback loops: logging, performance metrics, prompt iteration, and model evaluation
• Build MCP servers, CLIs and APIs and microservices that connect AI models to business systems: Salesforce, BigQuery, Slack, HubSpot, email, calendars, analytics tools
• Architect data flows that enable retrieval-augmented generation (RAG): connecting LLMs to internal knowledge bases, customer data in BigQuery, Salesforce data, and real-time business context
• Build serverless or containerized services (GCP Cloud Functions, Cloud Run, or similar) that scale with usage and integrate with Grafana's cloud infrastructure
• Scope high-impact automation problems autonomously by shadowing Sales, Customer Success, and Marketing teams to identify efficiency gaps
• Design and deploy automation workflows using tools like n8n, Zapier, Prefect, or custom orchestration platforms
• Build systems designed for self-service, with documentation and enablement materials that let others operate them independently
• Partner with GTM Analytics, Field Operations, Strategy & Planning, and GTM Systems teams to scope, prioritize, and refine use cases
• Collaborate with Data Engineering to source and structure relevant data for agentic and AI-enabled workflows
• Communicate technical constraints and trade-offs clearly to non-technical stakeholders across Revenue Operations and GTM leadership
• Establish and champion governance and compliance standards to AI workflows, including access controls, audit trails, and human-in-the-loop escalation path, setting the bar for responsible use of sensitive customer and business data