Staff Product Manager, Agent Observability

Responsibilities

• Own the observability roadmap: set a clear vision and sequenced plan for the suite (traces, recordings, dashboards, evals, quality metrics), decide what gets built and when in partnership with engineering.
• Ship products people rely on: turn complex, data-dense problems into experiences customers use every day and raise the bar on quality.
• Make agent quality measurable: build evals and metrics to determine if agents are good and improving (latency, cost, conversation quality, behavior).
• Design for two audiences: create a product that works for deeply technical engineers debugging calls and non-technical operators reviewing quality, cost, and behavior.
• Get deep with customers and data: understand how teams run and debug agents in production to shape priorities.
• Grow observability into a business: drive adoption and revenue so it reflects the value delivered to customers.

Requirements

• 8+ years in product management at a senior or staff level, ideally owning a developer-facing or data-heavy product.
• Technical depth: ability to reason about complex systems under the hood, earn trust of strong engineers, and make good tradeoffs (no coding required).
• Multi-persona product sense: experience building for both deeply technical users and non-technical users in the same product, with design judgment for dense, data-rich interfaces.
• Cross-functional influence: influence through clarity, trust, and judgment in a high-autonomy engineering environment.
• Communication skills: write clearly, present well, and move between board-level strategy and detailed technical discussions.
• Comfort with ambiguity: figure out what matters, prioritize ruthlessly, and move quickly in a small product team at a fast-growing company.

Nice-to-Haves

• Built an observability, monitoring, or analytics product, or a tool for evaluating and improving AI/LLM quality.
• Familiarity with evals, tracing, or quality measurement for AI/LLM or agent systems.
• Familiarity with debugging and monitoring software in production (logs, traces, metrics, dashboards).
• Background at a developer tools or infrastructure company.
• Familiarity with voice AI, real-time communication, or telephony.
• Experience with usage-based pricing models.