Level

PagerDuty

Senior AI/ML Engineer

PagerDuty is hiring a Senior AI/ML Engineer in Lisbon, Portugal. Level rates it ; you can apply on PagerDuty.

Level's read on this job

  • Level rates this machine learning engineer role Builds AI ●●●●: the job is building AI systems.
  • The posting mentions LangChain, LlamaIndex and LLMs among its tools and skills.
  • Level classes it as a senior role.
  • PagerDuty has 49 other open roles on Level.

AI in this role

Design, architect, and scale production AI systems, LLM agents, and retrieval pipelines for high-volume event streams.

langchainllamaindexllmsapis
ragai-agentsdistributed-systemsapplied-aiprompt-engineeringretrievalsystem-architecture

PagerDuty, Inc. (NYSE: PD) is the global leader in AI-first digital operations. By automatically detecting, diagnosing, and remediating issues, the PagerDuty Platform orchestrates AI agents and automated workflows with context from over 750 integrations. Trusted by approximately two-thirds of the Fortune 100 and nearly half of the Fortune 500, PagerDuty is the industry standard for organizations scaling resilient, autonomous operations. Notable customers include Chipotle, Cloudflare, Docusign, Fox, Nvidia, Salesforce, Spotify, Zoom and more. We are growing rapidly and hiring top talent with leading AI skills across engineering, sales, product, marketing, and beyond as we build the leading digital operations platform.

 

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.

How we rate this

Senior AI/ML Engineer at PagerDuty rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agentsDistributed SystemsApplied AIPrompt engineeringRetrievalSystem ArchitectureLangChain

Also common in machine learning engineer jobs at this level

Pay

Typical machine learning engineer job
$199k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. Tell me about a project where distributed systems was part of your work. What did you do?
  4. Tell me about a project where applied ai was part of your work. What did you do?
  5. How do you structure and test a prompt to get consistent output from a language model?

Adapt your resume

  • List these exact terms on your resume: RAG, AI agents, Distributed Systems, Applied AI, and Prompt engineering. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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