Staff AI Engineer

Role Overview

Join Grafana Labs’ Revenue Operations team as a Staff AI Engineer. You will own the AI agent infrastructure and automation platform powering go-to-market teams, with high autonomy and end-to-end ownership.

Key Missions

• Design and build multi-agent architectures and LLM integrations.
• Set the technical direction for the automation platform, including data models and API contracts.
• Partner with cross-functional teams to deliver scalable, self-service automation that improves operational efficiency.

Responsibilities

• Build multi-agent systems, agent orchestration patterns, and supporting infrastructure.
• Create backend services that connect AI models to internal and third-party data platforms.
• Implement production-grade LLM integrations with robust reliability and cost/latency controls.
• Deliver user-facing interfaces and tools that enable AI automation for GTM workflows.
• Drive collaboration by clearly communicating complex technical systems to both engineers and business stakeholders.

Requirements

• Strong proficiency in Python and JavaScript/Node.js, with Git-based workflows, code review, and testing discipline.
• Deep understanding of LLM failure modes and production mitigations, including:
  • confidence thresholds
  • fallback logic
  • human escalation
  • cost/latency management
• Google Cloud Platform experience, including BigQuery and serverless/containerized services (Cloud Functions, Cloud Run).
• Hands-on experience applying AI development tools (e.g., GitHub Copilot, Cursor, Claude Code).
• 8+ years of software engineering experience with backend/system integration or data/analytics depth.
• Experience with LLM frameworks and patterns such as:
  • prompt engineering
  • RAG
  • function calling/tool use
  • structured output parsing
  • evaluation
• 2+ years hands-on experience applying LLMs/AI to production workflows (not only prototypes).
• Ability to identify high-leverage problems, push back on low-impact requests, and deliver with minimal direction.

Nice-to-haves / Additional Signals

• Experience building and operating multi-agent systems at scale (orchestration, state management, production monitoring).
• Frontend/tooling experience for AI interfaces (e.g., React, Slack Block Kit, dashboard components).
• Familiarity with Revenue Operations / GTM Analytics / Sales Operations and tools such as Salesforce, HubSpot, Outreach, Gainsight.
• Experience with vector databases / retrieval pipelines (e.g., Pinecone, Weaviate, ChromaDB, pgvector).
• Experience with workflow automation platforms (e.g., n8n, Prefect, Clay, Apify, etc.).
• Exposure to observability tools for AI systems (e.g., LangSmith, Weights & Biases, custom logging/evaluation).
• Familiarity with Model Context Protocol (MCP) or similar standards.
• Prior work in open source or developer-focused SaaS companies.