Ground every answer in facts on this page and the original listing. We never invent Glassdoor-style reviews or salaries that are not in our data.
Expect deep dives on past AI systems you owned end-to-end, how you ground models in real telemetry, failure modes, and collaboration with platform teams. Read recent Grafana product news and be ready to discuss secure engineering given the reported token/codebase access incident.
Strong fit if you want senior AI work inside an open-source observability company, remote in Canada, and you are comfortable building on metrics/logs/traces rather than greenfield consumer apps. Data is thin on pay bands and formal career ladders—clarify those in process.
As a Senior AI Engineer at Grafana Labs, a typical day would center on AI features that sit on observability data: prototyping models or agents over metrics/logs/traces, integrating with Grafana’s data-source and dashboard stack, hardening prompts and evaluation, and pairing with product/platform engineers so AI outputs stay reliable at scale. Remote Canada hours mean async design notes, PR reviews, and incident-aware shipping discipline.
No cert family or priced resources were provided in CERTS. Prioritize production ML/LLM systems, Python/Go or similar, strong observability literacy (Prometheus, logs/traces), evaluation and safety for AI features, and experience shipping into large open-source or SaaS platforms.
Yes. The listing is Senior AI Engineer, Canada, remote (remote flag set).
Open-source Grafana dashboards and analytics over many data sources for metrics, logs, and traces (Wikipedia overview).
Grafana 13 launch coverage, reported fundraising at high valuation, and a 2026 codebase access incident via a leaked token—ask interviewers how engineering security practices evolved after that.
Website: grafanalabs.com
Grafana is an open-source analytics and visualization web application. It connects to time series databases and other data sources, allowing users to build dashboards that display metrics, logs, and traces. Grafana supports data sources including Prometheus, AWS CloudWatch, Graphite, InfluxDB, Elasticsearch, PostgreSQL, and MySQL.
Public cache only — not an employee review.
Grafana Labs is hiring a remote Senior AI Engineer in Canada to build and own the AI agent infrastructure that powers our Marketing Operations organization. If you turn LLMs into dependable production systems, this is a career-defining opportunity to shape technical direction end to end. About the Role As a Senior Engineer (AI & Automation), you will design multi-agent architectures, LLM integrations, and backend services that link AI models to internal and third-party data platforms. This is a high-autonomy position: you will surface the highest-leverage problems across Marketing, RevOps, and SDR teams, architect the solutions, and ship production systems that colleagues rely on every day. You'll set the technical direction for the automation platform — data models, API contracts, shared libraries, and reference architectures — collaborating with Data Engineering, GTM Systems, and Field Operations to deliver scalable, self-service automation. Key Responsibilities Own multi-agent AI systems from architecture and build through testing, deployment, and 24/7 operation using frameworks such as LangChain, CrewAI, or Anthropic MCP. Create reusable agentic skills invoked across Slack, dashboards, internal apps, and CLIs. Add observability and feedback loops — logging, performance metrics, prompt iteration, model evaluation, and cost control. Define governance for AI workflows: access controls, audit trails, PII handling, and human-in-the-loop escalation. Build MCP servers, APIs, CLIs, and microservices connecting LLMs to BigQuery, Slack, CRMs, email, calendars, and analytics tools, including RAG data flows. Deploy serverless and containerized services on GCP Cloud Functions and Cloud Run, plus workflows via n8n, Workato, or custom platforms with CI/CD and production reliability. Qualifications 8+ years in software engineering with depth in backend, systems integration, or data/analytics engineering. 2+ years applying LLMs to real production workflows, not prototypes. Strong Python and JavaScript/Node.js skills with disciplined Git workflows, code review, and testing. Hands-on experience with prompt engineering, RAG, function calling, structured output, and evaluation. Experience operating multi-agent systems at scale, including orchestration patterns and production monitoring. Deep familiarity with Google Cloud Platform, BigQuery, and serverless/containerized services. Fluency with AI-assisted development tools such as GitHub Copilot, Cursor, and Claude Code. About Grafana Labs Grafana Labs is the company behind the open observability…
Generated for personal interview prep · 2026-07-15 UTC · getajob.ai