Staff AI Engineer – Revenue Operations Automation

Job Overview

This role owns the technical direction of Grafana’s AI automation platform used by Revenue Operations. Working with Data Engineering, GTM Systems, Marketing, Field Operations, and Revenue leadership, you will identify high-impact operational problems, architect AI-powered solutions, and build production systems that teams rely on daily.

The position requires hands-on software engineering experience, deep knowledge of large language model technologies, multi-agent architectures, backend services, cloud infrastructure, and workflow automation.

Key Responsibilities

• Lead end-to-end development of production AI systems supporting Revenue Operations.
• Design, implement, test, deploy, and maintain multi-agent architectures.
• Develop modular AI agents using orchestration frameworks.
• Create reusable AI capabilities that operate across Slack, dashboards, command-line tools, and internal applications.
• Implement monitoring, logging, prompt evaluation, model assessment, performance measurement, and cost optimization.
• Establish governance practices including audit trails, access controls, human review workflows, and data protection standards.
• Develop APIs, microservices, command-line tools, and MCP servers connecting AI systems with business applications.
• Design retrieval-augmented generation pipelines integrating customer data, knowledge repositories, and business context.
• Develop serverless and containerized cloud services that integrate with Grafana’s infrastructure.
• Partner with Revenue Operations, Marketing, SDR, and Demand Generation teams to identify automation opportunities.
• Design workflow automation using orchestration platforms while maintaining production-quality engineering standards.
• Create documentation, playbooks, and enablement materials supporting self-service automation.

AI Engineering Responsibilities

• Develop production-ready multi-agent systems.
• Design orchestration workflows for sequential, parallel, and router-based agent execution.
• Implement retrieval-augmented generation architectures.
• Develop prompt engineering strategies and structured AI outputs.
• Build function-calling and tool integration capabilities.
• Manage AI state handling and production monitoring.
• Design confidence thresholds, fallback strategies, and human escalation workflows.
• Optimize latency, operational cost, and model performance.
• Use AI-assisted development tools to accelerate engineering productivity while maintaining code quality.

Required Qualifications

• At least 96 months of software engineering experience with strong backend, systems integration, or data engineering expertise.
• At least 24 months of hands-on experience applying large language models to production business workflows.
• Strong programming skills in Python.
• Strong programming skills in JavaScript or Node.js.
• Experience using Git-based development workflows, code reviews, and automated testing.
• Hands-on experience with prompt engineering, retrieval-augmented generation, structured outputs, function calling, and AI evaluation techniques.
• Experience designing and operating production multi-agent systems.
• Ability to analyze business processes before developing technical solutions.
• Strong knowledge of Google Cloud Platform.
• Experience with BigQuery.
• Experience developing Cloud Functions, Cloud Run services, or similar serverless and containerized applications.
• Understanding of AI reliability challenges including confidence scoring, fallback logic, human review, and cost optimization.
• Ability to independently identify high-value technical opportunities and deliver complete production solutions.
• Experience using AI-assisted software development tools such as GitHub Copilot, Cursor, or Claude Code.
• Excellent communication skills for both technical and business audiences.

Preferred Qualifications

• Experience building React applications or user interfaces for AI tools.
• Experience with Slack Block Kit.
• Knowledge of Salesforce, HubSpot, Outreach, Gainsight, or similar GTM platforms.
• Experience using vector databases including Pinecone, Weaviate, ChromaDB, pgvector, or comparable technologies.
• Background automating sales, marketing, or customer success workflows within B2B SaaS organizations.
• Experience with workflow automation platforms including n8n, Prefect, Clay, PhantomBuster, Apify, Dust, or similar tools.
• Knowledge of Model Context Protocol (MCP).
• Experience using observability platforms for AI systems such as LangSmith, Weights & Biases, or custom evaluation frameworks.
• Experience working within Revenue Operations or GTM Analytics organizations.
• Background in open-source or developer-focused software companies.

Technical Skills

• Python.
• JavaScript.
• Node.js.
• Large Language Models.
• Multi-agent systems.
• Retrieval-Augmented Generation (RAG).
• Prompt engineering.
• Model evaluation.
• Google Cloud Platform.
• BigQuery.
• Cloud Functions.
• Cloud Run.
• Backend APIs.
• Microservices.
• Workflow automation.
• Serverless computing.
• Containerized services.
• Git workflows.
• AI-assisted software development.

Work Arrangement

• Remote position within approved United States time zones.
• High-autonomy engineering role with significant ownership.
• Cross-functional collaboration with Revenue Operations, Data Engineering, GTM Systems, Marketing, and leadership teams.
• Strong focus on production software delivery and operational impact.

Compensation

The annual base salary range for this position is $174,986 to $220,000 USD.

Actual compensation depends on experience, interview assessment, technical skills, and overall qualifications.

Eligible employees also receive Restricted Stock Units (RSUs), bonus opportunities where applicable, and a comprehensive employee benefits package.

Benefits and Culture

• 100% remote global workplace.
• Collaborative open-source culture.
• High-trust environment with significant autonomy.
• Career growth opportunities.
• Company-wide transparency and approachable leadership.
• Annual leave policy including company shutdown days where applicable.
• In-person onboarding experience for new employees.
• Company-wide ownership through Restricted Stock Units.

About Grafana Labs

Grafana Labs develops observability software and cloud platforms that help organizations monitor applications, infrastructure, and operational data. Its open observability platform serves more than 35 million users and over 7,000 organizations worldwide, supporting reliability engineering, incident response, and telemetry management across modern cloud environments.