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About This RoleAI processing…
PagerDuty (NYSE:PD) is a leader in Digital Operations Management. In an always-on world, organizations of all sizes trust PagerDuty to help them deliver a perfect digital experience to their customers, every time. Teams use PagerDuty to identify issues and opportunities in real time and bring together the right people to fix problems faster and prevent them in the future. Over 13,000 organizations (including 60 of Fortune 100) rely on PagerDuty to succeed with Digital Transformation, Cloud Migration, and DevOps Modernization. Notable customers include GE, Cisco, Genentech, Electronic Arts, Cox Automotive, Netflix, Shopify, Zoom, DoorDash, Lululemon and more. We are expanding rapidly as a platform for Digital Operations Management using AI/ML and Automation and growing our adoption by Development, IT, Customer Service, Security, and other teams across the organization.
Key Responsibilities
- 1Design and build AI-powered features — LLM agents, retrieval, and event intelligence — that operate on high-volume, real-time event streams, from problem framing through production deployment and monitoring.
- 2Architect and own the systems behind them: agent and prompt orchestration, retrieval pipelines, tool/API integrations, and low-latency inference and evaluation at scale.
- 3Reason about consistency, throughput, fault tolerance, and cost across services that must stay reliable under bursty, unpredictable load.
- 4Take AI features from prototype to production, establishing the evaluation, guardrail, observability, and improvement loops that keep them accurate and trustworthy over time.
- 5Partner with platform, product, and applied-research teams to define what “good” looks like and to integrate AI cleanly into existing services.
- 6Raise the bar through example, reviews and mentorship, and help shape the team’s technical direction.
Requirements
- Experience with cloud infrastructure (AWS, GCP, or Azure), containers, and orchestration (Kubernetes).
- Strong communication and collaboration skills, and a track record of raising the quality of the teams and systems around you.
- Experience with LLMOps tooling and patterns — evaluation harnesses, prompt/version management, tracing and observability for agents, and online/offline eval consistency.
- Background in anomaly detection, event correlation, or applied problems in observability, AIOps, or reliability.
- Familiarity with the ecosystem — e.g. LLM APIs and frameworks such as LangChain or LlamaIndex, vector databases, and distributed data/compute tools such as Kafka, Airflow, or Spark.
- We are looking for a candidate who is genuinely passionate about building with modern AI — LLMs, agents, and retrieval — but grounded in the realities of building resilient, high-throughput systems.
- Nice to have Experience with LLMOps tooling and patterns — evaluation harnesses, prompt/version management, tracing and observability for agents, and online/offline eval consistency.
- Familiarity with the ecosystem — e.g.
- By submitting an application, you confirm that you have read and understand PagerDuty's Privacy Policy .
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