Grafana Labs currently has 18 active job listings related to AI. All of these roles are focused on agents, representing 100% of their AI hiring. The majority of these positions are in Engineering, with a smaller number in Product. The company is hiring for these roles in the United States and the United Kingdom. Their technical focus includes agent orchestration, LLM observability, RAG, tool use, and guardrails. Over the last 30 days, Grafana Labs has posted 2 new AI roles, a decrease of 86% compared to the previous 30-day period.
Currently tracking 9 active AI roles, down 65% versus the prior 4 weeks. Primary focus: Agent · Engineering.
Grafana Labs currently has 17 active AI-related roles in our index. The most common open titles are: Staff AI Engineer | Canada | Remote (2), Staff AI Engineer | US | Remote (2), Demand Generation Specialist | Canada | Remote, Demand Generation Specialist | United States | Remote, Director, Product Management - Data Collection, Transformation, and Ingest | Germany | Remote. Most positions are in Engineering and Product.
Grafana Labs's active AI hiring is concentrated in: agents (88%), application (12%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Grafana Labs is hiring AI talent in: United States (17 roles).
Job postings at Grafana Labs most frequently reference: agent orchestration, llm observability, rag, tool use, model serving.
In the past 30 days, Grafana Labs has posted 5 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Senior Solutions Engineer | Sweden | Remote This role is for a Senior Solutions Engineer at Grafana Labs, a company focused on open-source observability tools. The Solutions Engineer acts as a customer-facing product expert, enabling growth by educating customers, delivering technical presentations, and translating customer requirements into solutions using Grafana Labs technology. They partner with sales, provide feedback to product/engineering, and contribute to enablement materials. The role requires strong technical pre-sales experience, excellent communication skills, and a technical mindset. While the company works with observability data (metrics, logs, traces), the role itself is not directly building AI models but rather selling and supporting a product that may leverage AI or be used in AI-related contexts by customers. | — | 0 |