Description
Grafana Labs is seeking a Senior Backend Engineer to help build the first production services for a context layer management system. The ideal candidate will design and ship the core backend architecture that powers ingestion, context storage, retrieval APIs, and agent-facing integrations.
Key responsibilities:
- 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.
- 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.
- 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.
- 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.
- Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability.
- Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area.
- Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams.
- Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows.
Requirements:
- Experience with LLMs, prompt engineering, and building applications powered by GenAI.
- Proven track record of delivering software that made it into production and is actively used by users.
- Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure).
- Experience using observability tools to understand and troubleshoot system behavior.
Nice to have:
- Experience building or working with agent frameworks or multi‑agent workflows.
- Experience as a data analyst or work with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks).
- Experience building tools for data engineering.
In Canada, the Base compensation range for this role is CAD $164,490 - $197,389. Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits.