Senior AI/ML Engineer

PagerDuty; Lisboa; Presencial; EUR 90 000 - 135 000; Tempo integral

Resumo da oferta

PagerDuty is seeking a Senior AI/ML Engineer to build and scale AI-powered features across the Operations Cloud. You will own design and execution of LLM-powered agents, retrieval pipelines, and integration with existing services, delivering reliable, high-throughput AI capabilities in production.

You will work with platform, product, and applied research teams to ensure robust, guardrailed AI, and you will mentor teammates to raise overall team quality and technical direction.

Qualificações

• 5+ years of software engineering experience with production distributed systems.
• Hands-on experience building and shipping AI systems in production (LLMs, agents, retrieval).
• Strong programming fundamentals and ability to move between systems and AI code.
• Solid grounding in prompting, retrieval, agent patterns, and guardrails for LLMs.
• Experience with cloud infrastructure (AWS, GCP, or Azure), containers, and orchestration (Kubernetes).
• Pragmatic, reliability-minded mindset with scalable, correct systems.
• Strong communication and collaboration skills.

Responsabilidades

• Design and build AI-powered features (LLM agents, retrieval, event intelligence) operating on high-volume real-time streams.
• Architect and own agent orchestration, retrieval pipelines, tool/API integrations, and low-latency inference at scale.
• Ensure consistency, throughput, fault tolerance, and cost across services under bursty loads.
• Deliver production-grade AI features with evaluation, guardrails, observability, and improvements.
• Partner with platform, product, and research teams to align on goals and integration points.
• Mentor teammates and help shape the team's technical direction.

Conhecimentos

Distributed systems

AI systems production

Programming fundamentals

Applied AI fundamentals

Cloud infrastructure

Kubernetes

Reliability mindset

Communication

Ferramentas

AWS

GCP

Azure

Kubernetes

Descrição da oferta de emprego

About the role

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.

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