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Honeycomb.io

Observability platform for cloud applications

Senior Software Engineer 1 - Agent Observability

Full-Stack EngineeringConfirmed live in the last 24 hours
Full-timeRemote in CanadaRemote

About the Job

Requirements

  • Have at least 3 years of software engineering experience.
  • Have experience shipping customer-facing features at a Software-as-a-Service company, beyond internal tooling.
  • Have full-stack range, with proficiency in backend development using Go and/or Python and frontend development using TypeScript and React.
  • Have a track record of working with product managers and designers.
  • Regularly use artificial intelligence tools hands-on in day-to-day engineering work.
  • Have experience being on call; join the on-call rotation after about 90 days.
  • Have a track record of navigating ambiguity in a fast-moving field where requirements shift and experimentation is a core part of the job.

Responsibilities

  • Deliver artificial intelligence observability capabilities end to end, from ingestion to in-product visualizations.
  • Contribute to the data model and infrastructure that enable observing agents and their ecosystems across the product.
  • Build systems that analyze and surface artificial-intelligence-specific signals, such as cost, token usage, errors, and anomalies.
  • Collaborate with product and design partners to make sure what is built is usable, intuitive, and enables meaningful user workflows.
  • Share learnings about exploring and understanding artificial intelligence system behavior across conversations and workloads.
  • Iterate through fast feedback loops and experimentation, and share both successes and failures.

Desired Qualifications

  • Have experience building large language model or agent-powered features in production.
  • Have hands-on experience with observability tooling, such as OpenTelemetry.

About the Company

Honeycomb.io

Observability platform for cloud applications

Honeycomb.io provides a cloud observability platform for cloud applications. It collects telemetry data from applications and lets users query billions of events to understand performance and behavior. It uses Service Level Objectives (SLOs) to alert when customer experiences degrade, enabling teams to quickly debug issues. It offers tools like Query Builder, Query Assistant, and BubbleUp to analyze data and compare subsets against baselines. Its pricing is likely subscription or usage-based, charging based on data sent for analysis. The company differentiates itself by handling high-cardinality event data at scale with fast, flexible querying and by focusing on problem diagnosis and reliability for a wide range of customers. The goal is to help teams identify, debug, and optimize cloud applications to improve reliability and customer experience.

Company size
201-500
Company stage
Series D
Total funding
$146.9M
Headquarters
San Francisco, CA
Founded
2016

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