Staff AI Engineer | Canada | Remote

About the role

Grafana Labs seeks a Staff Engineer (AI & Automation) to own the AI agent infrastructure and automation platform for Marketing Operations. In this high-autonomy role, you will define technical direction, identify high-use problems, and deliver production systems used by teams daily. You will translate ambiguous problems into modular, production-ready multi-agent architectures. The position requires deep expertise in orchestrating complex agentic workflows and aligning them with business priorities at scale. You will act as a technical leader who challenges assumptions and drives best practices for AI engineering within the organization. Collaboration with cross-functional partners will be central to uncovering opportunities and turning them into automated, measurable solutions. This role is designed for an individual who thrives in ambiguous environments and can execute without direct oversight.

Key facts

What you'll do

Architect and implement end-to-end multi-agent systems using orchestration frameworks such as LangChain, CrewAI, and Anthropic MCP.

Build reusable agentic skills and behaviors invoked across dashboards, chat clients, command line interfaces, and internal applications.

Design and implement observability, logging, performance metrics, prompt iteration, model evaluation, and cost management for AI workflows.

Develop data flows for retrieval-augmented generation that connect large language models to internal knowledge bases, customer data, and real-time business context.

Create and expose APIs, MCP servers, CLIs, and microservices that connect AI models to business systems like BigQuery, Slack, CRMs, email, and calendar platforms.

Partner with RevOps, Demand Generation, Regional Marketing, and SDR teams to scope automation initiatives, identify bottlenecks, and define solutions with measurable business outcomes.

Deploy containerized or serverless services using GCP Cloud Functions and Cloud Run that integrate with Grafana Cloud and scale under load.

Establish governance and compliance standards covering access controls, audit trails, personally identifiable information handling, and human-in-the-loop escalation paths.

Evaluate emerging AI tools and frameworks to determine applicability and ROI for marketing-specific use cases.

Lead the design of agent memory systems, tool use capabilities, and deterministic workflows to improve reliability and performance.

Implement testing strategies for agent behaviors, including scenario-based evaluations and automated regression testing for AI pipelines.

Mentor engineers on prompt engineering, agent design patterns, and production ML operations within the marketing technology space.

Collaborate closely with product managers to translate business requirements into technical specifications for AI-driven features.

Continuously refine cost structures and latency budgets to ensure AI services remain efficient and sustainable at scale.

Requirements

Demonstrate hands-on experience building and operating multi-agent systems and orchestrating agentic workflows.

Show proven ability to design and implement retrieval-augmented generation patterns and data pipelines for large language models.

Have experience building and exposing APIs and MCP servers for AI model integration.

Exhibit strong judgment in designing systems that securely handle personally identifiable information.

Have a track record of shipping production backend services that integrate with third-party platforms at scale.

Possess deep proficiency in Python or TypeScript for implementing agent logic, integrations, and testing.

Bring experience with cloud platforms, particularly Google Cloud Functions and Cloud Run, for deploying serverless AI services.

Demonstrate familiarity with security and compliance best practices for handling sensitive data in AI applications.

Nice to have

Collaboration history with RevOps, Demand Generation, and Field Operations teams on automation initiatives.

Skills and tools

Proficiency with Grafana, BigQuery, Slack, Cloud Functions, Cloud Run, n8n, LangChain, CrewAI, and Anthropic MCP.

About the company

Grafana Labs, the company behind the open observability cloud, is founded on the principles of open source, open standards, open ecosystems, and open culture. Grafana Cloud, our fully managed observability platform, is flexible and built for scale. With Grafana Cloud's AI capabilities, organizations can see, understand, and act on disparate data to move at the speed of their ambitions. More than 35 million users and 7,000+ customers-including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce-trust Grafana Labs to ensure reliability of their applications, resolve incidents quickly, and optimize telemetry to reduce noise and cost. The company is 100% remote with over 1,600 team members across 40+ countries and is backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow updates on LinkedIn and X.