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Honeycomb.io

Observability platform for cloud applications

Staff Product Manager

Product ManagementConfirmed live in the last 24 hours
Full-timeRemote in Canada

About the Job

Requirements

  • At least 5 years of product management experience, including at least 1 year shipping AI/ML-powered products.
  • A track record of taking AI features from concept to customer impact, including learning from unsuccessful efforts.
  • Deep understanding of how engineering teams build, deploy, and operate AI systems.
  • Familiarity with current AI/ML techniques and judgment about when they are applicable.
  • Ability to synthesize research, customer feedback, and technical trends into coherent strategy.
  • Comfort operating with ambiguity and making decisions without perfect information.
  • Pattern recognition across customer conversations and ability to identify unclear emerging needs.
  • Strong judgment about when to defer or reject an approach despite exciting technology.
  • Sufficient technical depth to earn respect from engineers and architects.
  • Ability to evaluate trade-offs between AI approaches, including retrieval-augmented generation, fine-tuning, and model selection.
  • Understanding of observability principles and their importance in production systems.
  • Ability to explain complex ideas clearly to varied audiences.
  • Ability to influence across product, engineering, and go-to-market teams without formal authority.
  • Comfort presenting to customers, executives, and technical audiences.
  • Ability to stay current in fast-moving domains and learn with intellectual humility.

Responsibilities

  • Synthesize AI trends, customer needs, and technical capabilities into strategic recommendations.
  • Help the product organization distinguish where AI creates customer value from hype.
  • Identify emerging observability challenges created by AI adoption, such as large language model drift, prompt regression, and low-context generated code.
  • Assess which AI technologies and approaches warrant investment.
  • Build a deep understanding of how customers are adopting AI in engineering workflows.
  • Identify patterns in customer conversations that signal future market needs.
  • Monitor AI/ML developments, including retrieval-augmented generation, fine-tuning, and agentic systems, and translate their implications for observability.
  • Engage with technical communities, researchers, and early adopters to identify emerging trends.
  • Partner with product teams to identify valuable opportunities to use AI capabilities.
  • Guide teams on AI approaches, trade-offs, and best practices while allowing decisions to remain distributed.
  • Help teams understand how their work fits the broader AI strategy and how to use shared capabilities.
  • Synthesize cross-portfolio learnings and share what is and is not working.
  • Articulate Honeycomb's perspective on AI observability internally and externally.
  • Help customers understand how observability needs evolve as they adopt AI.
  • Contribute to thought leadership through writing, speaking, and community engagement.
  • Build credibility with technical audiences through considered use of AI.

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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