Grafana Labs
Senior AI Engineer| Canada| Remote
Rol remoto de Marketing con fit claro de ubicación del candidato.
PublicadoAgregado recientemente
Países elegibles2 países aceptados
Señal de senioritySenior
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
CanadáEstados Unidos
Resumen del rol
Senior AI Engineer| Canada| Remote
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
Details
- Own end-to-end development of multi-agent AI systems, from architecture and implementation through testing, deployment, and ongoing operation
- Build modular, composable agentic systems using orchestration frameworks (LangChain, CrewAI, Anthropic MCP, or similar) that operate 24/7 across teams
- Develop reusable agentic skills that agents invoke across interfaces (Slack, dashboards, internal apps, CLIs)
- 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 serverless or containerized services (GCP Cloud Functions, Cloud Run) that scale with usage and integrate with Grafana's cloud infrastructure
- Partner with RevOps, Demand Generation, Regional Marketing, and SDR teams to scope high-impact automation problems, identify bottlenecks, and build solutions with measurable business outcomes
- Design and deploy workflows using orchestration tools (n8n, Workato, or custom platforms) with CI/CD, testing, and production reliability standards
- Build systems designed for self-service with documentation, playbooks, and enablement materials that let partner teams operate independently
- 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. You think in workflows and outcomes, not just functions.
- Deep familiarity with Google Cloud Platform, BigQuery, and serverless/containerized services (Cloud Functions, Cloud Run)
- Understanding of LLM failure modes and production mitigations including confidence thresholds, fallback logic, human escalation, and cost/latency management
- Proven ability to identify high-leverage problems, push back on low-impact requests, and deliver end-to-end with minimal direction
- Fluent with AI-assisted development tools (GitHub Copilot, Cursor, Claude Code). You use AI to build AI systems
- Clear technical communicator who can explain complex systems in simple terms to both engineers and business stakeholders
- 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)
- Experience with workflow orchestration platforms (n8n, Temporal, Prefect, Airflow)
- 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. Grafana is built on OSS and we value engineers who share that DNA
- 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose.
- Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment.
- Transparent Communication – Expect open decision-making and regular company-wide updates.
- Innovation-Driven – Autonomy and support to ship great work and try new things.
- Open Source Roots – Built on community-driven values that shape how we work.
- Empowered Teams – High trust, low ego culture that values outcomes over optics.
- Career Growth Pathways – Defined opportunities to grow and develop your career.
- Approachable Leadership – Transparent execs who are involved, visible, and human.
- Passionate People – Join a team of smart, supportive folks who care deeply about what they do.
- In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it.
- Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable.
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