Honeycomb
Enterprise · Observability (OTel)
- HQ
- San Francisco, US
- Founded
- 2016
- Website
- honeycomb.io
Enterprise · Observability (OTel)
Currently tracking 1 active AI role, down 53% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $159k–$234k (avg $195k).
Honeycomb currently has 1 active AI-related role in our index. The most common open titles are: Senior Engineering Manager - Enablement. Most positions are in Engineering.
Honeycomb's active AI hiring is concentrated in: agents (100%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Honeycomb is hiring AI talent in: United States (1 role).
In the past 30 days, Honeycomb has posted 1 new AI-related role.
| Title | Stage | AI score |
|---|---|---|
| Senior Engineering Manager - Enablement Senior Engineering Manager to lead the Engineering Enablement team, focusing on equipping Honeycomb to innovate quickly and safely. This includes owning developer feedback loops (CI/CD, testing, tooling) and leading the incubation of AI-assisted engineering, particularly with the 'Autobots' platform of autonomous agents. The role requires experience in leading enablement teams, understanding AI tooling, and driving organizational change, with a focus on measuring developer productivity and satisfaction. | Agent | 7 |
| Senior Software Engineer - AI Intelligence Senior Software Engineer focused on AI Intelligence, specifically building and refining AI agents within the Canvas platform. The role involves full-stack development (Golang, React/TypeScript) for agent infrastructure, shipping AI product features, and owning software in production. Experience shipping products on top of LLMs or agents is required. | Agent |
| 7 |
| Senior Software Engineer - LLM Observability Senior Software Engineer focused on building the foundational layer for LLM observability within Honeycomb. This role involves designing and implementing backend systems and APIs in Go, contributing to full-stack features with React/TypeScript, and providing technical leadership. The core responsibility is to make AI workloads observable by defining how AI systems are represented in telemetry, normalizing data from various ecosystems into a consistent OpenTelemetry-based model, and owning the infrastructure and data model for downstream observability experiences. The role emphasizes ownership, collaboration, and technical leadership in a distributed environment. | Agent | 5 |