About this role
PagerDuty, Inc. (NYSE: PD) is the global leader in AI-first digital operations. By automatically detecting, diagnosing, and remediating issues, the PagerDuty Platform orchestrates AI agents and automated workflows with context from over 750 integrations. Trusted by approximately two-thirds of the Fortune 100 and nearly half of the Fortune 500, PagerDuty is the industry standard for organizations scaling resilient, autonomous operations. Notable customers include Chipotle, Cloudflare, Docusign, Fox, Nvidia, Salesforce, Spotify, Zoom and more. We are growing rapidly and hiring top talent with leading AI skills across engineering, sales, product, marketing, and beyond as we build the leading digital operations platform.
Senior Product Manager for AI and Automation
PagerDuty is redefining how modern engineering and operations teams work. PagerDuty’s Automation Platform includes Workflows, Actions, Connectors, and a growing agentic layer built on Skills and Tools. This is the backbone of how teams eliminate toil, respond to incidents autonomously, and ultimately enable AI-native SRE agents.
As Senior Product Manager for AI and Automation, you will own product strategy and execution across our Operations Cloud SaaS and on-premises automation products and lead the roadmap for the agentic automation experience we’re building for autonomous SRE agents. This is a high-visibility, high impact role that sits at the intersection of developer tooling, enterprise operations, and frontier AI product design.
You will report directly to the Senior Director of Product Management for the AI & Automation group and will partner tightly with engineering, design, GTM, and enterprise customers.
Key Responsibilities
• Define and drive the multi-year roadmap for Workflows and Actions, covering both cloud-delivered SaaS and on-premises deployments.
• Lead product definition for the agentic layer of PagerDuty’s automation platform — the Skills, Tools, and Connectors that enable AI agents to act autonomously in production environments.
• Define the model for how autonomous SRE agents interact with automation primitives: invoking runbooks, triggering Actions, calling external APIs via Connectors, and escalating when confidence is low.
• Work closely with engineering to define the trust, safety, and audit boundaries required before automation can act on behalf of an agent rather than a human.
• Partner with AI/ML teams and external model providers to ensure PagerDuty’s agentic experience is differentiated by domain — leveraging deep SRE context rather than generic automation.
• Own the customer-facing surface of agentic authorization — ensuring permissions, audit logs, and scoping controls are a natural and frictionless extension of current enterprise permissioning models.
• Identify and close gaps in the current platform by synthesizing customer feedback, usage data, competitive signals, and engineering constraints into a coherent strategy.