2 months ago
Lisbon, PortugalSenior
Responsibilities
- Design and build production AI features such as LLM agents, retrieval systems, and event intelligence for high-volume real-time event streams.
- Architect agent and prompt orchestration, retrieval pipelines, tool and API integrations, low-latency inference, and evaluation systems.
- Own the AI feature lifecycle from problem framing and prototyping through production deployment, monitoring, guardrails, and improvement loops.
- Design for consistency, throughput, fault tolerance, reliability, and cost under bursty and unpredictable loads.
- Partner with platform, product, and applied-research teams to define success criteria and integrate AI into existing services.
- Provide technical mentorship, participate in reviews, and help shape the team’s technical direction.
Requirements
- At least 5 years of software engineering experience, including meaningful experience building and operating production distributed systems.
- Hands-on experience building and shipping production AI systems, including LLM-powered applications, agents, or retrieval systems and their orchestration, serving, and evaluation components.
- Strong programming fundamentals and the ability to work across systems and AI/application code.
- Applied AI knowledge covering prompting, retrieval, agent patterns, LLM evaluation, and behavioral guardrails.
- Experience with cloud infrastructure such as AWS, GCP, or Azure, as well as containers and Kubernetes orchestration.
- Reliability-minded systems judgment and the ability to explain technical trade-offs.
- Strong communication and collaboration skills with a record of improving teams and systems.
- Preferred: experience with LLMOps, evaluation harnesses, prompt and version management, agent tracing and observability, and online/offline evaluation consistency.
- Preferred: experience with production LLM serving, retrieval-augmented generation, multi-step agents, tool use, anomaly detection, event correlation, observability, AIOps, or reliability.
- Preferred: familiarity with LLM APIs, LangChain, LlamaIndex, vector databases, Kafka, Airflow, or Spark, plus open-source AI or distributed-systems contributions.
Benefits
- Hybrid work model with flexibility within PagerDuty’s established office locations in Atlanta, Lisbon, London, San Francisco, Santiago, Sydney, Tokyo, and Toronto; candidates must reside in an eligible location.
- Competitive salary and comprehensive benefits package.
- Flexible work arrangements, company equity, and an Employee Stock Purchase Program, subject to eligibility.
- Retirement or pension plan, generous paid vacation, paid holidays, and sick leave.
- Dutonian Wellness Days and HibernationDuty companywide paid days off in addition to PTO.
- Paid parental leave of 22 weeks for a pregnant parent and 12 weeks for a non-pregnant parent, subject to local laws and eligibility.
- 20 hours of paid volunteer time off per year.
- Company-wide hack weeks and mental wellness programs.
Tech Stack
Categories
About PagerDuty
PagerDuty builds a subscription SaaS platform for incident response, on‑call management, AIOps, and workflow automation used by DevOps, IT, SRE, security, and support teams. Its cloud service centralizes alerts, orchestrates real-time response, and integrates with monitoring and ticketing tools. Founded in 2009 and headquartered in San Francisco, the public company (NYSE: PD) counts 60 of the Fortune 100 among its customers, including Netflix and Cisco.