Staff Product Manager - AI Team

Staff Product Manager - AI Team at honeycomb.io

Honeycomb is a service defining observability and raising expectations for developer tools. We work with well-known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard across various industries. This is an exciting time in our trajectory, having closed Series D funding, scaled past 200 people, and named to Forbes’ America’s Best Startups of 2022 and 2023. We encourage you to check out our blog posts and press releases for more insights.

We are a talented, opinionated, passionate, fiercely inclusive, and responsible group. We have conviction and strive to live our values every day, fostering a culture where people do what they love amongst highly talented, humble peers.

As a fully distributed company, we believe how you deliver matters most, not where you sit. We invest in our people, ensuring a strong orientation to our culture and processes, while providing trust, autonomy, and accountability from Day 1.

A Little More About The Team

You will be the product manager for our Canvas and Agentic AI teams, which are dedicated to building Honeycomb's AI-powered investigation experience. Canvas enables engineers to use natural language to query, visualize, and understand their production systems. We are moving beyond simple chat by building Skills (pre-configured workflows encoding domain expertise), Auto-Investigations (agent-driven investigations that initiate proactively), and a rearchitected Canvas that is both interactive and collaborative.

You will work closely with engineering and design leads, owning the roadmap for AI integration across Honeycomb, from the product UI to our MCP server. Partnering with our Director of AI Strategy, Research & Development teams, and customer-facing teams, you will stay grounded in customer needs while pushing for innovative, differentiated solutions. This role requires the ability to balance execution with navigating a product space where solutions 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 versus mere 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 a 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 their 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.
• Synthesize cross-portfolio learnings and socialize what's working (and what isn't).

• Evangelize the AI-observability connection.
• Articulate Honeycomb's point of view on AI observability both 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 who care deeply about how we use AI, not just that we use it.

What You’ll Bring To The Role

• Proven AI Product Experience: Experienced in product management with at least 1+ year shipping AI-powered products. Track record of taking AI features from concept to customer impact, including things that didn't work. Deep understanding of how engineering teams actually build, deploy, and operate AI systems (not just theoretical knowledge). Familiarity with current AI/ML techniques and the judgment to know when they're applicable versus overhyped.
• Strategic Thinking with Customer Empathy: Ability to synthesize disparate signals (research, customer feedback, technical trends) into coherent strategy. Comfort operating with ambiguity and making decisions without perfect information. Pattern recognition across conversations—spotting what customers aren't yet saying clearly. Strong judgment about when to say "no" or "not yet" despite exciting technology.
• Technical Credibility Without Needing to be the Expert: Enough technical depth to have earned respect from engineers and architects and the collaborative approach to drive work forward in tandem with the triad. Genuine curiosity about how things work, paired with humility about what you don't know. Ability to evaluate trade-offs between different AI approaches (RAG vs. fine-tuning, model selection, etc.). Understanding of observability principles and why they matter in production systems.
• Communication and Collaboration Skills: Excellent written and verbal communication—can explain complex ideas clearly to varied audiences. Ability to influence without authority across product, engineering, and go-to-market teams. Comfort presenting to customers, executives, and technical audiences. Collaborative mindset that elevates others' work rather than centralizing control.
• Curiosity and Learning Orientation: Demonstrated ability to stay current in fast-moving domains (AI is evolving weekly, not yearly). Intellectual humility—you're more interested in learning than being right. Excitement about the intersection of AI technology and real customer problems. Energized rather than exhausted by the pace of change in AI.

Key skills/competency

• AI Product Management
• AI Strategy
• Observability
• Natural Language Processing
• Agentic AI Systems
• Product Roadmap
• Customer Needs Analysis
• Technical Acumen
• Cross-functional Collaboration
• Market Research