Honeycomb
This role involves owning the end-to-end development of AI observability capabilities, from data ingestion to in-product visualizations, while architecting the underlying data model and infrastructure. The engineer will build systems to analyze AI-specific signals like cost and errors, collaborating with product and design teams to deliver intuitive features for debugging AI systems. The position requires a full-stack background with proficiency in backend and frontend technologies, along with hands-on experience using AI tools in daily engineering work.
Headquarters
San Francisco, California, United States
Company Size
51-200 employees
Founded
2016
Honeycomb is an observability platform for distributed services that gives engineering teams the context, speed, and scale they need to build and run cloud‑native and AI‑era software. It ingests high‑cardinality traces, metrics, and event data and exposes fast ad‑hoc querying, visualization, and debugging tools to accelerate root‑cause analysis and reduce MTTR. Honeycomb is available as a hosted service and private‑cloud option and includes capabilities like revamped metrics and Canvas for building dashboards and investigative workflows, aimed at SREs and developers working with microservices, serverless, and complex distributed systems.
Headquarters
San Francisco, CA
Company Size
201-500 employees
Founded
2018
Industry
Technology
Glassdoor Rating
4.2 / 5
Sarah Johnson
Chief Executive Officer
Michael Chen
Chief Technology Officer
Emily Williams
VP of Engineering
David Rodriguez
VP of Product
Jessica Thompson
Chief Financial Officer
Andrew Park
VP of Sales
View leadership team, funding history,
and employee contacts for Honeycomb.
26% above the average for this role
Honeycomb Raises $50 Million in Series D
Apr 7, 2023