GrafanaLabs is the company behind GrafanaCloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, GrafanaCloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on GrafanaLabs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.
Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. This is a remote opportunity and we are looking for candidates from Canada. Residents of Quebec are not eligible for this role. GrafanaLabs is seeking a Staff Engineer (AI & Automation) to own the AI agent infrastructure and automation platform that powers our Marketing Operations organization. You’ll build multi-agent architectures, LLM integrations, and backend services that connect AI models to internal and third-party data platforms. You’ll ship production systems that teams depend on daily. This is a high-autonomy role where you own the technical direction. You’ll identify the highest-leverage problems across Marketing, RevOps, and SDR teams, design the solutions, and ship them. You’ll define the technical direction for the automation platform (data models, API contracts, shared libraries, reference architectures) and partner with Data Engineering, GTM Systems,



and Field Operations to build scalable, self-service automation that eliminates manual work and drives operational efficiency. Agentic Systems & AI Infrastructure Own end-to-end development of multi-agent AI systems, from architecture and implementation through testing, deployment, and ongoing operation Implement observability and feedback loops including logging, performance metrics, prompt iteration, model evaluation, and cost management Establish governance and compliance standards for AI workflows including access controls, audit trails, PII handling, and human-in-the-loop escalation paths Build MCP servers, APIs, CLIs, and microservices connecting AI models to business systems (BigQuery, Slack, CRMs, email, calendars, analytics tools) Architect data flows for retrieval-augmented generation (RAG), connecting LLMs to internal knowledge bases, customer data, and real-time business context Build systems designed for self-service with documentation, playbooks, and enablement materials that let partner teams operate independently You'll have access to AI coding assistants (Claude Code, Gemini CLI, OpenAI Codex, and others of your choice within security guidelines). We encourage pragmatic AI-assisted development paired with strong code review and quality standards. 8+ years of software engineering experience with depth in backend development, systems integration,



or data/analytics engineering ~2+ years hands-on experience applying LLMs/AI to production workflows, not just prototypes ~ Strong proficiency in Python and JavaScript/Node.js with Git-based workflows, code review practices, and testing discipline ~ Hands-on experience with LLM frameworks and patterns including prompt engineering, RAG, function calling/tool use, structured output parsing, and evaluation ~ Experience building and operating multi-agent systems at scale including agent decomposition, orchestration patterns (sequential chains, router/dispatcher, parallel fan-out), state management, and production monitoring ~ You diagnose business problems before writing code. Fluent with AI-assisted development tools (GitHub Copilot, Cursor, Claude Code). You use AI to build AI systems ~ Transparent technical communicator who can explain complex systems in simple terms to both engineers and business stakeholders Bonus Points Experience with vector databases or retrieval pipelines (Pinecone, Weaviate, ChromaDB, Qdrant, pgvector) Familiarity with marketing or sales platforms (Salesforce, Customer.io, HubSpot, Marketo, Outreach) Experience with frontend frameworks (React, Slack Block Kit) for building user-facing AI tool interfaces Observability tooling for AI systems (LangSmith, Weights & Biases, custom evaluation frameworks) Familiarity with Model Context Protocol (MCP) or similar standards for connecting AI systems to data sources Prior work automating marketing, sales, or customer success workflows in a B2B SaaS environment Active in open-source communities. In Canada, the base compensation range for this role is CAD 164,490 – CAD 197,389. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana L

📌 Staff AI Engineer | Canada | Remote
🏢 Grafana
📍 Canada