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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
- 1Contribute to AI-powered features — LLM agents, retrieval, and event intelligence — that operate on high-volume, real-time data, with support and guidance from senior engineers.
- 2Help build and maintain the systems behind them — prompt and agent orchestration, retrieval pipelines, tool/API integrations, and inference services — writing code, adding tests, and improving observability.
- 3Learn to reason about latency, throughput, cost, and reliability of LLM-powered services, and apply those lessons in the code you write.
- 4Help take AI features from prototype toward production, and support the evaluation and monitoring loops that keep them accurate and trustworthy over time.
- 5Partner with platform, product, and applied-research teams, asking good questions and turning requirements into working code.
- 6Grow through code review, pairing, and mentorship, and steadily take on more ownership as you develop.
Requirements
- 2+ years of software engineering experience building and shipping production software.
- Degree in CS/a related field, or equivalent practical experience.
- Solid programming fundamentals and comfort moving between application code and AI/model code.
- Hands-on experience with modern AI — building something real with LLMs, prompting, retrieval, or agent frameworks.
- Some exposure to distributed systems and how software runs reliably at scale, and eagerness to deepen it.
- Strong communication and collaboration skills.
Perks & Benefits
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