Staff Backend Engineer - Second Horizon | Canada | Remote

Grafana Labs Grafana Labs · Data AI · Canada · Remote · R&D: Second Horizon

Staff Backend Engineer to build the core backend architecture for an AI-native data intelligence system that provides AI agents with governed access to enterprise context. This involves designing and shipping services for ingestion, storage, retrieval APIs, and agent integrations, focusing on scalability, multi-tenancy, and operational reliability.

What you'd actually do

  1. Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration.
  2. Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries.
  3. Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings.
  4. Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production.
  5. Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability.

Skills

Required

  • Strong engineering skills
  • Solid experience building production-grade, user-facing software systems
  • Self-starter, capable of tackling complex engineering problems
  • Familiar with AI technologies and frameworks
  • Experience with backend development
  • Experience with SaaS architecture
  • Experience with observability tools (metrics, logs, traces)
  • Experience with cloud platforms
  • Experience with distributed systems

Nice to have

  • Experience with agent frameworks
  • Experience with RAG systems
  • Experience with vector databases
  • Experience with data governance

What the JD emphasized

  • build the first production services for this context layer management system
  • design and ship the core backend architecture
  • early-stage role on a high-autonomy team
  • comfortable working through ambiguity
  • making pragmatic architectural decisions
  • building systems that can evolve from internal dogfooding to production-grade SaaS
  • familiar with AI technologies and frameworks
  • focus on delivering high-quality solutions that work in the real world, not just in theory
  • comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset
  • take ownership and drive projects forward
  • pushing boundaries to find the most impactful solutions
  • deal with ambiguity
  • define scope where things are loosely defined

Other signals

  • AI-native data intelligence system
  • context layer management system
  • AI agents retrieve context