Why This Job is Featured on The SaaS Jobs
PagerDuty’s focus on AI and automation sits in a core SaaS category: operations platforms that become embedded in how engineering organisations run production. This role is notable because it spans both cloud-delivered SaaS and on-premises deployments, a common reality for enterprise DevOps buyers. The remit also touches an emerging SaaS frontier, agentic automation, where product decisions must balance capability with control in real-world production environments.
For a SaaS product leader, the long-term value here is exposure to platform-style product management rather than single-feature ownership. Workflows, actions, and connectors create an ecosystem surface area that rewards strong thinking about APIs, integration strategy, and product telemetry. The agentic layer adds a modern SaaS learning curve around trust, safety, authorisation, and auditability, which are increasingly reusable skills across AI-enabled B2B products.
This role tends to suit product managers who enjoy technical domains and can translate between SRE practitioners, security stakeholders, and engineering teams. It also fits someone comfortable shaping multi-year roadmaps while grounding decisions in customer feedback and operational constraints. Candidates motivated by infrastructure-adjacent SaaS and enterprise-grade product trade-offs will find the scope aligned with that trajectory.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
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.
Basic Qualifications
- 5+ years of product management experience shipping customer-facing software at scale; SaaS B2B strongly preferred.
- Deep fluency in the SRE and DevOps domain — you understand how on-call rotations work, what makes a runbook effective, and what it means to operate production systems.
- Hands-on experience with workflow automation, integration platforms, job schedulers, or infrastructure tooling.
- Ability to think clearly about authorization models — you don’t need to write policy engine code, but you must be able to reason about principals, permissions, scopes, and trust delegation in conversations with security architects and enterprise customers.
- Strong technical aptitude: comfortable reading API specs, digging into telemetry, and holding substantive conversations with senior engineers.
- Track record of managing ambiguous, multi-stakeholder roadmaps from vision through GA.
- Excellent written and verbal communication; can distill complex platform trade-offs for both technical and executive audiences.
- Familiarity with UI/UX best practices, usability testing, and interpreting user research to inform roadmap decisions and feature development
- Track record of building positive working relationships with engineering, UX design and teams outside of product development
- Passion for getting things done (and for things you haven’t done, you are naturally curious, driven to learn, and unafraid to ask for help)
- Strong customer empathy and a curiosity-driven approach to learning their needs.
Preferred Qualifications
- Experience building or shipping AI/ML-powered product features, LLM integrations, or agentic systems.
- Prior work with authorization frameworks.
- Background at an observability, incident management, or ITSM company.
- Familiarity with on-premises or hybrid deployment models (Kubernetes operators, air-gapped environments, enterprise security reviews).
- Experience with connector/integration ecosystems or low-code/no-code builder products.
- MBA a plus
