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Frequently asked questions

  • What AI roles is Honeycomb hiring for?

    Honeycomb currently has 2 active AI-related roles in our index. The most common open titles are: Senior Software Engineer - AI Intelligence, Senior Software Engineer - LLM Observability. Most positions are in Engineering.

  • What stage of AI development does Honeycomb focus on?

    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.

  • Where is Honeycomb hiring AI talent?

    Honeycomb is hiring AI talent in: United States (1 role), Canada (1 role).

  • What technologies does Honeycomb's AI team work with?

    Job postings at Honeycomb most frequently reference: llm observability, agent orchestration, model serving, rag, evals.

  • How many AI roles has Honeycomb posted recently?

    In the past 30 days, Honeycomb has posted 2 new AI-related roles.

Jobs (2)

1 AI · 17 total active
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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.
AgentEngineeringUnited States, Canada · Remote4d ago7
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
Engineering
United States · Remote
3w ago
5