# Senior AI/ML Engineer

**Company:** [PagerDuty](https://hotfix.jobs/companies/pagerduty)
**Location:** Lisbon, Portugal
**Role:** ML Engineering
**Experience:** 5+ years
**Skills:** LLMs, AI Agents, Retrieval-Augmented Generation, Prompt Engineering, Kubernetes, Cloud Infrastructure, Distributed Systems, Event-Driven Architecture, AWS, GCP, Azure, LangChain, Llamaindex, Vector Databases, Kafka
**Posted:** 2026-08-20

> Build and operate production AI systems, including LLM agents, retrieval pipelines, and event intelligence, across PagerDuty’s high-scale distributed platform. The role requires 5+ years of software engineering experience, production distributed-systems expertise, and hands-on experience shipping reliable LLM applications.

## Job Description

## Responsibilities
- Design and build AI-powered features, including LLM agents, retrieval, and event intelligence, for high-volume real-time event streams.
- Architect and own agent and prompt orchestration, retrieval pipelines, tool/API integrations, and low-latency inference and evaluation systems.
- Design for consistency, throughput, fault tolerance, reliability, and cost under bursty, unpredictable loads.
- Take AI features from prototype to production with evaluation, guardrails, observability, and continuous improvement loops.
- Partner with platform, product, and applied-research teams to define quality standards and integrate AI into existing services.
- Provide technical leadership through code reviews, mentorship, and shaping technical direction.

## Requirements
- 5+ years of software engineering experience, including substantial experience building and operating production distributed systems.
- Experience with high-throughput services, streaming or event-driven architectures, or large-scale data platforms.
- Hands-on experience building and shipping production AI systems, including LLM applications, agents, or retrieval systems and their orchestration, serving, and evaluation.
- Strong programming fundamentals and ability to work across systems and AI/application code.
- Knowledge of prompting, retrieval, agent patterns, and evaluating and guardrailing LLM behavior.
- Experience with cloud infrastructure, containers, and Kubernetes.
- Reliability-oriented mindset and ability to explain technical trade-offs.
- Strong communication and collaboration skills.

## Nice to Have
- Experience with LLMOps tooling, evaluation harnesses, prompt and version management, agent tracing, and observability.
- Experience serving LLM systems in production, including retrieval-augmented generation, multi-step agents, and tool use.
- Background in anomaly detection, event correlation, observability, AIOps, or reliability.
- Familiarity with LangChain, LlamaIndex, vector databases, Kafka, Airflow, or Spark.
- Contributions to open-source AI or distributed-systems projects.

## Compensation and Benefits
- Competitive salary.
- Comprehensive benefits package.
- Flexible work arrangements.
- Company equity and ESPP, where eligible.
- Retirement or pension plan.
- Paid vacation, holidays, and sick leave.
- Wellness days and companywide paid days off.
- Paid parental leave and volunteer time off.
- Company hack weeks and mental wellness programs.

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