Top Engineering Jobs

Design, build, and operate scalable software services supporting insurance shopping, booking, servicing, and claims. Lead complex technical initiatives, make architectural decisions, integrate AI/ML solutions, and ensure reliability, security, observability, and performance. Mentor engineers, collaborate across product and engineering teams, define metrics, and drive continuous improvement across distributed systems and customer-facing platforms.

Design, develop, test, deploy, monitor, and improve backend services and customer experiences for Expedia’s Home & Navigation team. Responsibilities include low-level system and API design, data modeling, service integrations, operational reliability, incident resolution, metrics-driven optimization, and responsible integration of AI/ML capabilities. The role collaborates with product, design, and engineering teams to deliver scalable, secure, maintainable, and highly observable services.

Leads a team of 10–12 Workday engineers and platform specialists while owning Workday capabilities, platform operations, roadmap execution, implementations, integrations, security, governance, reliability, and continuous improvement. Partners with HR, Finance, Payroll, Product, and Technology leaders to translate business priorities into scalable solutions, develop engineering standards, manage team capacity and performance, and identify AI and automation opportunities.

Lead and develop a team of Workday engineers and platform specialists; own Workday capabilities, operations, roadmap, architecture, integrations, security, reliability, and governance. Drive implementations, enhancements, releases, transformation initiatives, automation, AI adoption, and continuous improvement. Partner with HR, Finance, Payroll, Product, Technology, and senior stakeholders to translate business priorities into scalable solutions and measurable outcomes while managing team capacity, performance, and career growth.

Design, build, and operate scalable, high-performance backend services and APIs. Lead architecture, code reviews, and cross-team integrations. Integrate AI/ML responsibly, diagnose and resolve production issues, and participate in on-call rotations to maintain operational excellence.

Design, develop, test, and maintain scalable Java/Kotlin software features and microservices for Expedia Group’s B2B travel agent platform. The role involves architectural contributions, API and distributed-systems development, production troubleshooting, code reviews, cross-functional collaboration, and improving engineering practices, tooling, reliability, and performance.

Design, build, and maintain scalable Android applications using Kotlin and modern Android frameworks. Lead end-to-end feature delivery, including API design, data modeling, backend integration, testing, and deployment. Collaborate with product, design, and engineering teams to deliver high-quality mobile experiences. Improve code quality, architecture, observability, performance, and incident resolution while safely integrating AI/ML-enabled capabilities. Mentor engineers and drive architectural improvements across Android applications.

Provides technical leadership for Expedia Group’s content platforms, defining backend and full-stack architecture for scalable content acquisition, enrichment, curation, and delivery. Designs AWS cloud-native systems, REST and gRPC APIs, data models, and distributed services. Establishes engineering standards for testing, deployment, reliability, observability, and operational excellence across multiple teams. Guides cross-functional architecture decisions and the safe production integration of AI and machine learning capabilities. Requires 10+ years of experience and French-English bilingualism.

Build cloud-native, real-time AI-powered fraud decisioning and remediation systems. Partner with Data/ML scientists and engineering teams to integrate AI, benchmark solutions, automate operations, and monitor production services at scale.

Operate and optimize AI-enabled production systems in AWS, ensuring reliability, availability, performance, security, and observability. Build automation, infrastructure-as-code, tooling, and runbooks for deployments, incident response, recovery, and change management. Collaborate with software, platform, data, and ML teams on model-serving infrastructure, APIs, background processing, and data pipelines. Use operational metrics and insights to reduce toil, improve resilience, and safely integrate AI/ML capabilities into production.