Staff Backend Engineer, Grafana

Grafana Labs

Staff Backend Engineer building production services for Grafana’s context layer management system. Seeking strong engineering skills and AI experience in a remote role based in Ireland.

Posted 7/23/2026full-timeRemote • 🇮🇪 IrelandLead💰 €117,600 - €141,120 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong engineering skills with a focus on building scalable SaaS architectures and AI-driven applications. Proficient in using observability tools for system reliability and effective communication in collaborative environments.

Highest-signal resume keywords

Strong Engineering SkillsAI ExperienceExperience with LLMsCloud-Native EnvironmentsObservability Tools

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Backend Service DesignAPI DevelopmentContext IngestionContext IndexingRetrieval OrchestrationMulti-Tenant ArchitectureUsage TrackingQuotas ManagementPrompt EngineeringSoftware Delivery

Soft Skills

Effective CommunicationCollaborative AttitudeProven Initiative

Tools & Technologies

AWSGCPAzureObservability Tools

Industry Keywords

SaaSAI SolutionsCloud-NativeSystem AdministrationService Boundaries

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud Platform

About the role

Key responsibilities & impact

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

What you’ll need

Strong engineering skills
AI experience with a practical mindset
Quick iteration and experimentation
Proven initiative
Collaborative attitude
Experience with LLMs, prompt engineering, and building applications powered by GenAI
Proven track record of delivering software that made it into production
Exposure to working in cloud-native environments (AWS, GCP, Azure)
Experience using observability tools to understand and troubleshoot system behavior

Benefits

Comp & perks

Equity
Bonus (if applicable)
30 days annual leave
In-person onboarding for new hires