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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. About the role PagerDuty’s Operations Cloud runs on a platform that ingests billions of signals and turns them into real-time action for thousands of customers. We’re looking for a Senior AI/ML Engineer who lives at the intersection of two disciplines: large-scale distributed systems and applied AI. In this role you will design and ship AI systems that run in production at PagerDuty’s scale — powering Incident Management AI Agents, event intelligence, and the LLM-powered capabilities embedded across our platform. You’ll own the full lifecycle, from framing the problem to serving reliably at scale. 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. What you’ll do Design 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. Architect and own the systems behind them: agent and prompt orchestration, retrieval pipelines, tool/API integrations, and low-latency inference and evaluation at scale. Reason about consistency, throughput, fault tolerance, and cost across services that must stay reliable under bursty, unpredictable load. Take AI features from prototype to production, establishing the evaluation, guardrail, observability, and improvement loops that keep them accurate and trustworthy over time. Partner with platform, product, and applied-research teams to define what “good” looks like and to integrate AI cleanly into existing services. Raise the bar through example, reviews and mentorship, and help shape the team’s technical direction. What you’ll bring 5+ years of software engineering experience, with meaningful time spent building and operating production distributed systems (high-throughput services, streaming/event-driven architectures, or large-scale data platforms). Hands-on experience building and shipping AI systems in production — LLM-powered applications, agents, or retrieval — including the surrounding orchestration, serving, and evaluation, not just prototypes. Strong programming fundamentals and comfort moving between systems and AI/application code. Solid grounding in applied AI fundamentals: prompting, retrieval, agent patterns, and how to evaluate and guardrail LLM behavior. Experience with cloud infrastructure (AWS, GCP, or Azure), containers, and orchestration (Kubernetes). A pragmatic, reliability-minded mindset: you optimize for systems that work correctly at scale, and you can articulate the trade-offs behind your choices. Strong communication and collaboration skills, and a track record of raising the quality of the teams and systems around you. Nice to have Experience with LLMOps tooling and patterns — evaluation harnesses, prompt/version management, tracing and observability for agents, and online/offline eval consistency. Deep experience serving LLM-based systems in production, including retrieval-augmented generation, multi-step agents, and tool use. 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. Contributions to open-source AI or distributed-systems projects. Why PagerDuty At PagerDuty, AI it’s core to how we help the world’s teams keep their digital services running. You’ll work on problems where scale, latency, and correctness genuinely matter, alongside engineers who care about building systems that people depend on in their most critical moments. Hesitant to apply? We encourage you to submit your resume even if you don't meet every requirement. We value potential and consider each candidate's full professional story. Whether you're exploring a career change or taking your next step, we look forward to reviewing your application. If this just isn’t the right role or time - sign up for job alerts ! Where we work PagerDuty operates a hybrid work model with offices in 8 major cities: Atlanta, Lisbon, London, San Francisco, Santiago, Sydney, Tokyo, and Toronto. While we offer flexibility within our established locations, we cannot employ candidates residing in: Location restrictions: Australia: Northern Territory, Queensland, South Australia, Tasmania, Western Australia Canada: Alberta, Manitoba, Newfoundland, Northwest Territories, Nunavut, PEI, Quebec, Saskatchewan, Yukon United States: Alaska, Hawaii, Iowa, Louisiana, Mississippi, Nebraska, New Mexico, Oklahoma, Rhode Island, South Dakota, West Virginia, Wyoming Candidates must reside in an eligible location, which vary by role. How we work Our values guide how we support customers, collaborate with colleagues, develop products, and foster a culture of belonging. They define not just our actions, but what it means to be Dutonian. People Leaders at PagerDuty are responsible for creating high performance environments that drive accountability. PagerDuty has four key dimensions that define our Leadership Impact: Lead Self, Lead the Team, Lead the Business, and Lead the Future. Each dimension has three associated competencies to give leaders a shared language for guiding their development, career, promotion, and succession planning discussions. Our Manager Expectations serve as a practical guide for managers to understand their responsibilities, prioritize their efforts, and drive engagement and performance. What we offer As a global organization, our total rewards approach is competitive with industry standards and aligned with local laws and regulations. Learn more, including country-specific offerings, on our benefits site . Your package may include: Competitive salary Comprehensive benefits package Flexible work arrangements Company equity* ESPP (Employee Stock Purchase Program)* Retirement or pension plan* Generous paid vacation time Paid holidays and sick leave Dutonian Wellness Days & HibernationDuty - companywide paid days off in addition to PTO Paid parental leave: 22 weeks for pregnant parent, 12 weeks for non-pregnant parent (some countries have longer leave standards and we comply with local laws)* Paid volunteer time off: 20 hours per year Company-wide hack weeks Mental wellness programs *Eligibility may vary by role, region, and tenure About PagerDuty PagerDuty, Inc. (NYSE:PD) is a global leader in digital operations management. The PagerDuty Operations Cloud is an AI-powered platform that empowers business resilience and drives operational efficiency for enterprises. With a generative AI assistant at its core, PagerDuty empowers teams to detect and resolve issues in real time, orchestrate complex workflows, and drive continuous improvement across their digital operations. Trusted by nearly half of both the Fortune 500 and the Forbes AI 50, as well as approximately two-thirds of the Fortune 100, PagerDuty is essential for delivering always-on digital experiences to modern businesses PagerDuty is Great Place to Work-certified™, a Fortune Best Workplace for Millennials, a Fortune Best Medium Workplace, a Fortune Best Workplace in Technology, and a top rated product on TrustRadius and G2. Go behind-the-scenes on our careers site and @pagerduty on Instagram. Additional Information PagerDuty is an equal opportunity employer. PagerDuty does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, parental status, veteran status, or disability status. Your privacy is important to us. By submitting an application, you confirm that you have read and understand PagerDuty's Privacy Policy . PagerDuty is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application process. Should you require accommodation, please email accommodation@pagerduty.com and we will work with you to meet your accessibility needs. PagerDuty uses the E-Verify employment verification program.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.