Product Manager

Dash0 is a company focused on redefining observability through AI-driven solutions. They are seeking a Product Manager to own the goals, metrics, and roadmap for their autonomous AI product, collaborating closely with engineers, designers, and stakeholders to drive its success.

Responsibilities:

• Set the goals, then hit them - define the KPIs that matter for an autonomous agent, align targets with leadership, and steer a senior engineering and design team against them, through data and logic rather than authority
• Run the operating rhythm for your area in close partnership with the Director of Product - planning, prioritization, and keeping alignment across levels and with the other product verticals
• Own the roadmap end-to-end - from discovery through launch - across the two modes: Chat, which runs investigations when engineers ask, and, Automations, which runs them without anyone asking
• Drive the commercial side: shape task-based credit pricing and packaging, and partner directly with sales on our technical buyers
• Conduct deep customer discovery with SREs, on-call engineers, and platform teams - understand their workflows well enough to challenge your own assumptions
• Demo the full Dash0 platform and talk to customers about it - at Dash0 this is the bar for every team member, and as PM you set the example in demos and sales cycles
• Be a credible external voice - speak at events, publish opinions, engage the OTel, SRE, and AI engineering communities

Requirements:

• A track record of delivering outcomes, not output: you make things happen, steer others toward results, and are comfortable signing up for goals you can only reach through your team
• Exceptional communication: you articulate product vision and rationale convincingly to engineers, designers, executives, and customers - and you keep levels and functions aligned without needing authority to do it
• Demonstrable product taste - products you have shipped that people point to, and strong opinions about why agentic products succeed or fail on UX and trust, not just capability
• Drive and learning velocity: you do not need to be an observability or AI expert today, but you work with AI tools hands-on, you are visibly on a steep curve, and you can point to a domain you mastered fast before
• Customer-facing strength: confidence demoing the full platform - not just your own product area - and holding your own in a technical sales conversation
• Track record shipping an AI/LLM product to production: you have lived with evals, non-determinism, model regressions, and cost-per-task economics
• Observability and incident-response depth - you have built at or competed with Datadog, Grafana, Honeycomb, New Relic, or the Instana-era APM generation, understand why OpenTelemetry-native matters, and can earn an SRE's respect in the first conversation
• Hands-on with the agent stack: MCP, eval frameworks, agent orchestration, context engineering - ideally you have built agents or automations yourself
• Experience with usage- or consumption-based pricing (credits, tasks, tokens) and with a PLG motion running alongside an enterprise sales cycle
• Familiarity with enterprise trust topics for autonomous systems: data handling, sandboxed execution, compliance
• Has shipped in an early-stage or high-growth company - not just big tech with infinite runway