Staff GTM Engineer (AI & Automation)
This is a remote opportunity and we are looking for candidates from the U.S.
The Opportunity
Grafana Labs is seeking a Staff GTM Engineer (AI & Automation) to build our next-generation AI agent and workflow systems. You'll spend most of your time writing code — designing multi-agent architectures, integrating LLM APIs, building data pipelines, and shipping automation that runs 24/7 across Marketing, RevOps, and SDR teams. Ideal for a builder who thrives at the intersection of AI, automation, and business growth.
You'll execute the AI growth roadmap, building internal capabilities and integrations that streamline marketing and operational workflows across teams. You'll implement multi-agent systems that drive results across Marketing, RevOps, and SDR teams. With strong technical ability and execution focus, you'll deliver AI-first solutions that translate business bottlenecks into comprehensive, automated systems that drive measurable ROI, accelerate growth, and elevate team effectiveness across departments.
This is a hands-on builder role with 60-70% coding and systems development, and 30-40% operational enablement (requirements, documentation, training, measurement, and stakeholder alignment). You’ll be a key driver of Grafana’s internal AI transformation by implementing governance and delivering automation that accelerates marketing and go-to-market efficiency.
What You'll Be Doing
Build & operate GTM automation systems
Build and operate reliable automation across custom code + orchestration tools (e.g., n8n/Workato/Make), including CI/CD, testing, deployment practices, and runbooks that keep iteration fast and safe
Implement modular, scalable, multi-agent AI systems that operate 24/7 and integrate with marketing platforms (e.g., Customer.io, Marketo, Salesforce, BigQuery)
Own technical direction for GTM automation: design data models, define API contracts, build shared libraries, and maintain reference architectures used across teams
Review code, write tests, and maintain production reliability standards
Operate, enable, and scale GTM workflows
Partner with RevOps, Demand Generation, Regional Marketing, Events Marketing, & SDRs to solve workflow inefficiencies through agent-based solutions with measurable business outcomes
Create reusable workflow templates, playbooks, and “how-to” docs so partner teams can safely self-serve common automations (with clear ownership and measurement)
Provide hands-on technical support and troubleshooting for AI systems across teams
Key Strategic Project: AI Chatbot Routing & Human-in-the-Loop Orchestration
Align AI chatbot systems across multiple teams (Marketing, SDR, Customer Success) to create unified prospect interaction routing
Build intelligent routing logic that determines when and how to engage human resources in prospect interactions
Implement tracking and analytics to measure routing effectiveness and refine human-in-the-loop triggers
Create scalable patterns for prospect intent classification and optimal channel/resource assignment
Define SLAs, failure modes, and fallback pathways (when routing is uncertain, when systems are down, when confidence is low)
Instrument end-to-end funnel metrics (handoff time, qualification accuracy, meeting set rate, pipeline influence) and iterate
AI Implementation & Operational Excellence
Build and maintain secure, documented systems with robust PII controls, compliance protocols, and permission frameworks
Implement company-wide standards for AI prompt engineering, version control, testing, observability, and business impact measurement
Create internal training materials, best practices documentation, and scalable frameworks for AI tools that enable cross-functional team success
Support ongoing AI adoption through hands-on technical assistance and system optimization
What Makes You a Great Fit
Technical Proficiency
7+ years building production systems and integrations (software engineering, data/analytics engineering, business systems, or GTM engineering)
2+ years hands-on experience applying LLMs/AI to production workflows — not just prototypes
Proven experience delivering AI-enabled systems or automation (0→1 or major expansions) with measurable business outcomes
Strong in Python and JavaScript/Node.js with Git-based development workflows, code review practices, and testing discipline
Deep familiarity with Google Cloud Platform, BigQuery, and Cloud Functions
Hands-on experience with LLM frameworks and patterns: prompt engineering, RAG, function calling/tool use, agent orchestration, structured output parsing, and evaluation
Fluent with AI-assisted development tools (GitHub Copilot, Cursor, Claude Code) — you use AI to build AI systems
Systems Implementation & Operational Excellence
Experience implementing automation systems, building agent workflows, and maintaining scalable infrastructure
Proven ability to execute, prioritize, and deliver high-ROI AI automation projects
Strong documentation skills and ability to communicate clearly with technical and business audiences
Experience integrating with Salesforce (or similar CRM) and at least one marketing automation platform (Customer.io / HubSpot / Marketo)
Background working with analytics, segmentation, and personalization platforms
Mindset & Approach
A hands-on builder who helps others thrive, where you ship solutions and enable colleagues to build on your work
Comfortable working in ambiguity with high autonomy and you scope your own work, follow through on commitments, and default to transparency when making technical decisions
Favors progress over perfection by shipping iteratively, learn from production, and improve continuously
Seeks diverse perspectives when designing systems, gather input from the teams who'll use what you build, not just the ones who requested it
AI & Agent Systems
Experience building multi-agent systems: agent decomposition, orchestration patterns (sequential chains, router/dispatcher, parallel fan-out), state management across handoffs
Understanding of LLM failure modes and production mitigations: confidence thresholds, fallback logic, human escalation, cost/latency management
Experience with systematic LLM evaluation: golden datasets, regression testing, A/B testing prompts, monitoring for drift
Familiarity with conversational AI, chatbot development, and routing logic
Bonus Points
Background in B2B SaaS or GTM operations
Active in open-source communities
Experience with workflow orchestration platforms (n8n, Temporal, Prefect, Airflow)
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.
About the job
Apply for this position
Staff GTM Engineer (AI & Automation)
This is a remote opportunity and we are looking for candidates from the U.S.
The Opportunity
Grafana Labs is seeking a Staff GTM Engineer (AI & Automation) to build our next-generation AI agent and workflow systems. You'll spend most of your time writing code — designing multi-agent architectures, integrating LLM APIs, building data pipelines, and shipping automation that runs 24/7 across Marketing, RevOps, and SDR teams. Ideal for a builder who thrives at the intersection of AI, automation, and business growth.
You'll execute the AI growth roadmap, building internal capabilities and integrations that streamline marketing and operational workflows across teams. You'll implement multi-agent systems that drive results across Marketing, RevOps, and SDR teams. With strong technical ability and execution focus, you'll deliver AI-first solutions that translate business bottlenecks into comprehensive, automated systems that drive measurable ROI, accelerate growth, and elevate team effectiveness across departments.
This is a hands-on builder role with 60-70% coding and systems development, and 30-40% operational enablement (requirements, documentation, training, measurement, and stakeholder alignment). You’ll be a key driver of Grafana’s internal AI transformation by implementing governance and delivering automation that accelerates marketing and go-to-market efficiency.
What You'll Be Doing
Build & operate GTM automation systems
Build and operate reliable automation across custom code + orchestration tools (e.g., n8n/Workato/Make), including CI/CD, testing, deployment practices, and runbooks that keep iteration fast and safe
Implement modular, scalable, multi-agent AI systems that operate 24/7 and integrate with marketing platforms (e.g., Customer.io, Marketo, Salesforce, BigQuery)
Own technical direction for GTM automation: design data models, define API contracts, build shared libraries, and maintain reference architectures used across teams
Review code, write tests, and maintain production reliability standards
Operate, enable, and scale GTM workflows
Partner with RevOps, Demand Generation, Regional Marketing, Events Marketing, & SDRs to solve workflow inefficiencies through agent-based solutions with measurable business outcomes
Create reusable workflow templates, playbooks, and “how-to” docs so partner teams can safely self-serve common automations (with clear ownership and measurement)
Provide hands-on technical support and troubleshooting for AI systems across teams
Key Strategic Project: AI Chatbot Routing & Human-in-the-Loop Orchestration
Align AI chatbot systems across multiple teams (Marketing, SDR, Customer Success) to create unified prospect interaction routing
Build intelligent routing logic that determines when and how to engage human resources in prospect interactions
Implement tracking and analytics to measure routing effectiveness and refine human-in-the-loop triggers
Create scalable patterns for prospect intent classification and optimal channel/resource assignment
Define SLAs, failure modes, and fallback pathways (when routing is uncertain, when systems are down, when confidence is low)
Instrument end-to-end funnel metrics (handoff time, qualification accuracy, meeting set rate, pipeline influence) and iterate
AI Implementation & Operational Excellence
Build and maintain secure, documented systems with robust PII controls, compliance protocols, and permission frameworks
Implement company-wide standards for AI prompt engineering, version control, testing, observability, and business impact measurement
Create internal training materials, best practices documentation, and scalable frameworks for AI tools that enable cross-functional team success
Support ongoing AI adoption through hands-on technical assistance and system optimization
What Makes You a Great Fit
Technical Proficiency
7+ years building production systems and integrations (software engineering, data/analytics engineering, business systems, or GTM engineering)
2+ years hands-on experience applying LLMs/AI to production workflows — not just prototypes
Proven experience delivering AI-enabled systems or automation (0→1 or major expansions) with measurable business outcomes
Strong in Python and JavaScript/Node.js with Git-based development workflows, code review practices, and testing discipline
Deep familiarity with Google Cloud Platform, BigQuery, and Cloud Functions
Hands-on experience with LLM frameworks and patterns: prompt engineering, RAG, function calling/tool use, agent orchestration, structured output parsing, and evaluation
Fluent with AI-assisted development tools (GitHub Copilot, Cursor, Claude Code) — you use AI to build AI systems
Systems Implementation & Operational Excellence
Experience implementing automation systems, building agent workflows, and maintaining scalable infrastructure
Proven ability to execute, prioritize, and deliver high-ROI AI automation projects
Strong documentation skills and ability to communicate clearly with technical and business audiences
Experience integrating with Salesforce (or similar CRM) and at least one marketing automation platform (Customer.io / HubSpot / Marketo)
Background working with analytics, segmentation, and personalization platforms
Mindset & Approach
A hands-on builder who helps others thrive, where you ship solutions and enable colleagues to build on your work
Comfortable working in ambiguity with high autonomy and you scope your own work, follow through on commitments, and default to transparency when making technical decisions
Favors progress over perfection by shipping iteratively, learn from production, and improve continuously
Seeks diverse perspectives when designing systems, gather input from the teams who'll use what you build, not just the ones who requested it
AI & Agent Systems
Experience building multi-agent systems: agent decomposition, orchestration patterns (sequential chains, router/dispatcher, parallel fan-out), state management across handoffs
Understanding of LLM failure modes and production mitigations: confidence thresholds, fallback logic, human escalation, cost/latency management
Experience with systematic LLM evaluation: golden datasets, regression testing, A/B testing prompts, monitoring for drift
Familiarity with conversational AI, chatbot development, and routing logic
Bonus Points
Background in B2B SaaS or GTM operations
Active in open-source communities
Experience with workflow orchestration platforms (n8n, Temporal, Prefect, Airflow)
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.
