Job description

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 that 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. Lodging Connectivity is the API- and software-driven backbone of our supply business, simplifying connectivity across lodging products through external-facing APIs and platforms that enable partners to acquire, optimize, and maintain lodging supply. We are an AI-forward team: we use AI across how we design, build, test, and operate software, and we are building AI-enabled capabilities into our services. In this role, you will deliver traveler, partner, and company value with stable architecture, high quality, and operational excellence, and you will help set the bar for how our team uses AI responsibly and effectively. In this role, you will: Design, build, and evolve reliable backend services, including system design (LLD), API design, and data modeling for scalable, secure, and maintainable solutions. Use AI coding assistants and agentic workflows as part of your daily engineering practice (design exploration, code generation, test authoring, refactoring, code review, debugging, and incident triage), and critically validate the output for correctness, security, and maintainability. Design and ship AI/ML-enabled capabilities in backend services, such as LLM-powered features, agent and tool integrations, and retrieval or automation workflows, with attention to latency, cost, quality evaluation, and failure modes. Define and promote team practices for responsible AI adoption: prompt and context management, evaluation and guardrails, data privacy, and compliance with EG security policies. Implement high-quality production code with an emphasis on automated testing, observability, performance, and operational excellence. Collaborate with product, design, and partner engineering teams to translate customer and business requirements into robust backend solutions, reusable service integrations, and well-structured data flows. Own the end-to-end lifecycle of services and features: development, testing, deployment, monitoring, troubleshooting, and incident resolution. Use data, metrics, experimentation, and analytics to prioritize work, validate hypotheses, and measure the impact of both product changes and AI-driven improvements to engineering productivity. Mentor engineers on effective, safe use of AI tooling and raise the team’s overall velocity and quality. Minimum Qualifications : Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience. 8 years of professional experience building and operating production backend services in a team environment. Demonstrated ownership of services or features across design, implementation, quality, deployment, and operational support. Strong software engineering fundamentals: data structures, algorithms, system design (LLD), API design, and data modeling, applied in production systems. Hands-on, demonstrable proficiency with AI-assisted development: you can describe specific workflows where AI tools measurably improved your speed or quality, and where they failed and how you caught it. Hands-on experience integrating AI/ML or LLM capabilities into a production system (for example, calling model APIs, building tool or agent integrations, or operating ML-backed services). Preferred Qualifications : Experience designing and evolving multi-service backend architectures with well-structured APIs, data models, and reliable data flows. Demonstrated success improving high-traffic or customer-facing systems through performance tuning, resilience hardening, and reliability engineering. Strong operational excellence: instrumentation, logging, metrics, alerting, on-call participation, and incident response. Experience with experimentation, feature flags, A/B testing, and analytics to guide technical and product decisions. Experience with LLM application patterns (RAG, tool calling/MCP, agent orchestration), evaluation frameworks, and observability for AI systems (token cost, latency, quality drift). Experience building AI guardrails: input/output validation, prompt-injection mitigation, PII handling, and human-in-the-loop controls. Experience driving AI tooling adoption across a team, including playbooks, shared prompts or agent configurations, and measuring impact. The total cash range for this position in Seattle is $184,500.00 to $258,000.00. Employees in this role have the potential to increase their pay up to $295,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future. Benefits and perks Expedia Group offers benefits and perks designed to support employees and their families, including medical, dental, and vision coverage, paid time off, an Employee Assistance Program, wellness and travel reimbursement, travel discounts, and International Airlines Travel Agent Network (IATAN) membership. Learn more about life at Expedia Group at careers.expediagroup.com . Accommodation requests Expedia Group is committed to providing an inclusive and accessible recruiting experience. If you need an accommodation or adjustment due to a disability during the application or recruiting process, please submit a request at expedia.service-now.com job_accommodation . About Expedia Group Expedia Group includes three flagship consumer brands - Expedia, Hotels.com, and Vrbo - along with a leading B2B travel business and travel advertising offerings. Across our brands and business, we help travelers explore the world with confidence and ease. Important notice Employment opportunities and job offers at Expedia Group will always come from Expedia Group s Talent Acquisition and hiring teams. Never share sensitive personal information unless you are confident of the recipient. Expedia Group does not extend job offers via email or messaging tools to individuals with whom we have not made prior contact. Our email domain is expediagroup.com. The official place to find and apply for roles is careers.expediagroup.com . Equal Opportunity Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other characteristic protected by law. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.

Requirements

Must-haves

Design, build, and evolve reliable backend services, including system design (LLD), API design, and data modeling for scalable, secure, and maintainable solutions.
Define and promote team practices for responsible AI adoption: prompt and context management, evaluation and guardrails, data privacy, and compliance with EG security policies.
Implement high-quality production code with an emphasis on automated testing, observability, performance, and operational excellence.
Collaborate with product, design, and partner engineering teams to translate customer and business requirements into robust backend solutions, reusable service integrations, and well-structured data flows.
Own the end-to-end lifecycle of services and features: development, testing, deployment, monitoring, troubleshooting, and incident resolution.
Use data, metrics, experimentation, and analytics to prioritize work, validate hypotheses, and measure the impact of both product changes and AI-driven improvements to engineering productivity.
Mentor engineers on effective, safe use of AI tooling and raise the team’s overall velocity and quality.
Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience.
8 years of professional experience building and operating production backend services in a team environment.
Demonstrated ownership of services or features across design, implementation, quality, deployment, and operational support.
Strong software engineering fundamentals: data structures, algorithms, system design (LLD), API design, and data modeling, applied in production systems.
Hands-on, demonstrable proficiency with AI-assisted development: you can describe specific workflows where AI tools measurably improved your speed or quality, and where they failed and how you caught it.
Hands-on experience integrating AI/ML or LLM capabilities into a production system (for example, calling model APIs, building tool or agent integrations, or operating ML-backed services).

Nice-to-haves

Experience designing and evolving multi-service backend architectures with well-structured APIs, data models, and reliable data flows.
Demonstrated success improving high-traffic or customer-facing systems through performance tuning, resilience hardening, and reliability engineering.
Strong operational excellence: instrumentation, logging, metrics, alerting, on-call participation, and incident response.
Experience with experimentation, feature flags, A/B testing, and analytics to guide technical and product decisions.
Experience with LLM application patterns (RAG, tool calling/MCP, agent orchestration), evaluation frameworks, and observability for AI systems (token cost, latency, quality drift).
Experience building AI guardrails: input/output validation, prompt-injection mitigation, PII handling, and human-in-the-loop controls.
Experience driving AI tooling adoption across a team, including playbooks, shared prompts or agent configurations, and measuring impact.
Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningapiaimlllm

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

Paid Time Off

Wellness