Grafana Labs - Staff GTM Engineer (AI & Automation) | Canada | Remote

• 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