Senior Backend Engineer - Analytics
New
G
Grafana LabsObservability, data intelligence
This is a remote opportunity and we are looking for candidates from the U.S. or Canada. Residents of Quebec are not eligible for this role.Full-TimeSenior
Salary154,445 - 185,334 USD per year
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Job Details
- Required Skills
- AWSGCPAzurePrompt EngineeringGenerative AI
Requirements
- Have experience with LLMs, prompt engineering, and building applications powered by GenAI.
- Have a track record of delivering software that reached production and is actively used by users.
- Have exposure to cloud-native environments such as AWS, GCP, or Azure.
- Have experience using observability tools to understand and troubleshoot system behavior.
- Be comfortable releasing prototypes, collecting feedback, and iterating.
- Be able to take ownership, work through ambiguity, and define scope where requirements are loosely defined.
- Communicate effectively and collaborate with peers.
- Nice to have: experience building or working with agent frameworks or multi-agent workflows.
- Nice to have: experience as a data analyst or working with data platforms such as Looker, Tableau, Power BI, Snowflake, or Databricks.
- Nice to have: experience building tools for data engineering.
Responsibilities
- Design, implement, test, and operate services for context ingestion, indexing, retrieval orchestration, API access, source configuration, and system administration.
- Help build a multi-tenant SaaS architecture with tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries.
- Build APIs and service interfaces for AI agents, MCP tools, CLIs, and internal applications to retrieve context, provenance, confidence signals, and warnings.
- Partner with the team to balance experimentation and long-term reliability as the project moves from prototype to production.
- Instrument services with metrics, logs, traces, alerts, and dashboards, and use observability tools to improve reliability.
- Help shape architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices.
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