Software Development Engineer III (backend + Devops)

Expedia Expedia · Hospitality · Gurgaon, India

Software Development Engineer III (Backend + Devops) at Expedia, focusing on the continuous delivery platform. The role involves designing and implementing backend services, driving operational excellence, and collaborating with cross-functional teams. While the team is exploring AI/ML to improve the delivery ecosystem, the core of this role is in backend development and DevOps, not direct AI/ML model building.

What you'd actually do

  1. Own, design, and implement medium-to-large scale services and features, including system design (low-level design), API design, and data modeling to support highly available, performant travel platforms.
  2. Write clean, testable, and maintainable code across the full software development lifecycle, including unit, integration, and contract tests, ensuring high quality and reliability in production.
  3. Collaborate with product, design, and cross-functional engineering teams to decompose complex business problems, define clear technical solutions, and deliver customer-centric outcomes across multiple domains.
  4. Drive operational excellence for your services by defining SLIs/SLOs, improving observability, and implementing robust monitoring, alerting, and incident response practices.
  5. Safely integrate and operate AI/ML‑enabled solutions that improve outcomes, including familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products.

Skills

Required

  • Bachelor’s degree in Computer Science or related technical field or equivalent professional experience
  • 5+ years of relevant professional experience
  • Building and operating backend or full-stack services
  • Production service ownership
  • Proficiency in at least one modern programming language and associated frameworks
  • RESTful API design
  • Data modeling
  • System design (low-level design) for distributed services
  • Full service lifecycle ownership (design, development, testing, deployment, operations)
  • CI/CD pipelines
  • Source control
  • Cloud-based environments

Nice to have

  • Designing and evolving service architectures in large-scale, distributed environments
  • Thoughtful API contracts
  • Schema design
  • Performance optimization
  • Reducing incidents
  • Improving latency
  • Increasing reliability
  • Metrics
  • Observability tooling
  • Data-driven decision making
  • Integrating AI/ML-enabled components or services
  • Ensuring safe operation
  • Guardrails
  • Measurable impact on customer or business outcomes
  • Working across multiple domains or tech stacks
  • Learning new technologies
  • Shared frameworks, libraries, or platforms
  • Leading technical delivery for complex projects
  • Influencing design decisions
  • Mentoring others
  • Secure, scalable coding practices
  • Familiarity with AI-driven systems, tools, or workflows
  • Applying AI/ML concepts to real world products

What the JD emphasized

  • AI/ML-enabled solutions
  • AI-driven systems
  • applying AI/ML concepts