Staff Product Manager - AI Team
Confirmed live in the last 24 hours
Honeycomb
Compensation
$220,000 - $250,000/year
Job Description
A little more about the team:
You'll be the product manager for our Canvas and Agentic AI teams - the teams building Honeycomb's AI-powered investigation experience. Canvas lets engineers use natural language to query, visualize, and understand their production systems. We're pushing well past chat: we're building Skills (pre-configured workflows that encode domain expertise into repeatable, executable actions), Auto-Investigations (agent-driven investigations that kick off before a human gets paged), and a rearchitected Canvas that's both interactive and collaborative.
You'll work in a tight triad with engineering and design leads, owning the roadmap for how AI shows up in Honeycomb, from the product UI to our MCP server. You'll partner with our Director of AI Strategy, Research & Development teams, and our customer-facing teams to stay grounded in what customers actually need while pushing toward something meaningfully different from what exists today.
This is a role for someone who can hold both execution and ambiguity: shipping production features while navigating a product space where the right answers are still emerging.
What you’ll do in the role:
Define AI product strategy in service of Honeycomb's vision
- Synthesize AI trends, customer needs, and technical capabilities into clear strategic recommendations
- Help the product organization understand where and how AI creates genuine customer value vs. where it's hype
- Identify emerging observability challenges created by AI adoption (e.g., LLM drift, prompt regression, low-context generated code)
- Make informed bets about which AI technologies and approaches warrant investment
Conduct research that bridges technology and customer reality
- Build deep understanding of how customers are adopting AI in their engineering workflows
- Identify patterns across customer conversations that signal future market needs
- Stay current with AI/ML developments (RAG, fine-tuning, agentic systems, etc.) and translate implications for observability
- Engage with technical communities, researchers, and early adopters to spot trends before they go mainstream
Enable AI innovation across the product portfolio
- Partner with product teams to identify high-value opportunities to leverage AI capabilities
- Provide guidance on AI approaches, trade-offs, and best practices without centralizing all decisions
- Help teams understand how their work fits into our broader AI strategy and how to leverage shared capabilities
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