Cloud Infrastructure Development Engineer III - Kubernetes

Expedia•Chicago, IL

1d•Onsite

About The Position

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business. Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere. Introduction to Team Our Technology Team partners with teams across Expedia Group to create innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction. This Cloud Infrastructure Development Engineer III role is part of the cloud infrastructure team which sits within our technology division. The cloud infrastructure team designs, builds, and operates the foundational cloud platforms, tools, and services that power Expedia Group’s products at global scale, ensuring they are secure, reliable, and cost-efficient.

Requirements

Bachelor’s degree in Computer Science or a related technical field; or Equivalent related professional experience.
5+ years of relevant professional experience.
3+ years of infrastructure automation, configuration management or container orchestration
Experience building, deploying, and operating cloud infrastructure or platform services, with ownership spanning multiple services or engineering teams.
Proficiency with software engineering and cloud-platform practices, including automation, infrastructure as code, APIs, data modeling, observability, and reliability engineering.
Demonstrated proficiency with at least one major public cloud provider, container orchestration concepts, networking, and security controls, including hands-on experience with infrastructure-as-code and automation.
Proficiency in at least one programming language such as Python, Go, or Java.

Nice To Haves

Experience designing and operating cloud platforms at scale with strong availability, performance, security, and cost characteristics.
Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real-world products.
Experience designing and implementing Service Mesh within Kubernetes environments, including strong knowledge of Istio and familiarity with emerging architectures such as Ambient Mesh.
Advanced proficiency developing Kubernetes-related tooling, controllers, operators, or automation using Go (Golang).
Proficient with Terraform for provisioning, automating, and managing cloud and Kubernetes infrastructure at scale.
Solid understanding of systems engineering and networking fundamentals, including proxy-based architectures, workload identity and authentication, service-to-service communication, and TCP/IP networking concepts within cloud environments.
Experience with cloud-native infrastructure tooling and frameworks such as Crossplane, Terragrunt, cert-manager, Kubernetes Load Balancer Controllers, or similar technologies used to support scalable and secure platform operations.
Prior experience creating, maintaining, and troubleshooting Kubernetes manifests, Helm charts, and YAML-based configurations.

Responsibilities

Design, build, and operate reliable cloud platform capabilities that enable engineering teams to deliver and run services effectively.
Apply technical aptitude across infrastructure, automation, observability, security, and platform reliability to improve engineering outcomes.
Configure, implement, and enhance service mesh capabilities, including ingress controller patterns and Istio-based solutions, to support secure service-to-service communication and workload connectivity.
Drive observability, capacity planning, system and service performance analysis, and environment tuning, while debugging issues across production and pre-production environments.
Advance continuous delivery practices by automating application and infrastructure deployments, integrating infrastructure as code into CI/CD pipelines, and detecting and remediating deployment issues.
Take ownership of high-pressure operational scenarios by applying calm, data-driven decision making, advocating for operational excellence through resiliency, scalability, testing, and service-level practices, participating in on-call rotations, and exploring new technologies, including AI-driven tools and workflows, that improve engineering outcomes.
Safely integrate and operate AI/ML-enabled solutions that improve outcomes, while applying AI/ML concepts to real-world products and workflows.