Staff Backend Engineer
Staff Backend Engineer building an AI-native data intelligence and context system for Grafana to enable reliable enterprise data access for AI agents. Requires strong production backend experience, practical GenAI/LLM skills, cloud-native expertise, and comfort with ambiguity on an autonomous early-stage team.
About the job
Key Responsibilities
- Build core backend services for context ingestion, indexing, retrieval orchestration, API access, source configuration, and system administration.
- Create scalable SaaS foundation including multi-tenant architecture, tenant isolation, usage tracking, quotas, audit logs, background jobs, and service boundaries.
- Power agent-facing retrieval workflows by building APIs and interfaces for AI agents, MCP tools, CLIs, and internal applications to access context, provenance, confidence signals, and warnings.
- Partner across product and infrastructure teams to balance fast experimentation with long-term reliability as the project moves from prototype to production.
- Operate services by instrumenting with metrics, logs, traces, alerts, and dashboards; use observability tools to monitor and improve reliability.
- Contribute to technical direction by shaping architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices.
- Communicate effectively in a dynamic, collaborative environment and take full ownership of developed AI solutions to ensure they are innovative, scalable, maintainable, and aligned with user workflows.
Requirements
- Strong experience building production-grade, user-facing software systems; self-starter capable of tackling complex problems with minimal supervision.
- Experience with LLMs, prompt engineering, and building applications powered by GenAI.
- Proven track record of delivering software into production that is actively used by users.
- Exposure to cloud-native environments (e.g., AWS, GCP, Azure).
- Experience using observability tools to understand and troubleshoot system behavior.
- Practical AI mindset focused on delivering high-quality, real-world solutions.
- Comfortable with quick iteration, releasing prototypes, collecting feedback, and working through ambiguity.
- Proven initiative, ownership, and ability to drive projects forward.
- Collaborative attitude with effective communication and openness to feedback.
Nice-to-Haves
- Experience building or working with agent frameworks or multi-agent workflows.
- Experience as a data analyst or with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, Databricks).
- Experience building tools for data engineering.
Skills
LLMs, Prompt Engineering, Generative AI, AWS, GCP, Azure, Observability Tools, Python, Go
Similar jobs
Backend Engineering jobs
Grafana Labs
United States
Staff backend engineer responsible for evolving Grafana into a scalable, multi-tenant observability application platform. The role requires production operations experience, distributed-systems expertise, strong communication, and familiarity with Go or willingness to learn it.
Turion Space
Irvine, CA
Leads architecture and development of mission-critical backend systems for spacecraft command, telemetry, mission planning, and operations. Requires 8+ years of software development experience, distributed-systems and cloud-native expertise, and technical leadership.
United States
Leads the technical direction and hands-on development of scalable backend platforms for Pinterest’s AI-driven products. Requires extensive backend and distributed-systems experience, strong Python skills, production LLM or ML experience, and cross-functional technical leadership.
United States
Leads the technical strategy, architecture, and operation of Pinterest’s large-scale storage infrastructure supporting SQL and graph workloads. Requires 8+ years of backend distributed-systems experience, technical leadership, and expertise in production reliability, performance tuning, and modern database technologies.
Censys
United States
Designs and operates Internet-scale scanning, DNS, attribution, and data pipelines, with deep ownership of distributed backend systems and production reliability. Requires 10+ years of software engineering experience, strong Go expertise, cloud and streaming infrastructure knowledge, and the ability to mentor engineers.