$116,500 – $163,000
Listed on Expedia Group’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
This role leads the design and operation of cloud infrastructure and AI systems for Expedia's enterprise platform, partnering across teams to build scalable, secure, and cost-efficient services. It suits senior engineers who excel at architecting complex systems, reducing operational toil through automation, and mentoring others while navigating the intersection of platform engineering and AI workflows.
Our summary, not Expedia Group’s wording. The full posting is on their site.
Skills this role names
- Amazon Web Services (AWS)
- Go
- Kubernetes
- Microsoft Azure
- Pulumi
- Python
- Retrieval-Augmented Generation (RAG)
- Salesforce
- ServiceNow
- Terraform
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What they ask for
Required
- 5+ years infrastructure, platform, or enterprise systems engineering experience (or 3+ years with Master's degree)
- Bachelor's degree or equivalent practical experience in relevant field
- Hands-on design-level experience with AWS, Azure, or GCP (compute, networking, storage, IAM)
- Infrastructure-as-Code ownership with Terraform, Pulumi, or equivalent, including reusable modules and policy-as-code
- Proficiency in Python, Go, or similar language with automation track record
- Experience designing SaaS and enterprise system integration architectures
- SLO definition and observability engineering (telemetry, synthetic testing, alerting)
- AI/ML literacy including LLMs, RAG, agentic systems, and production AI guardrails
- Experience with enterprise AI copilot or knowledge-assistant platform administration and integration
- Service or integration architecture ownership including security and operability design
- Technical communication ability for architecture decision records and design documents
Nice to have
- Enterprise SaaS administration and integration at scale (Glean, ServiceNow, Salesforce)
- Leadership or contribution to platform team engineering standards and golden paths
- Mentorship of less experienced engineers
- Open-source infrastructure tooling or internal developer platform contributions
- Experience embedding AI/automation into operational workflows
- FinOps practices familiarity