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About This Role
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 the Team
Expedia Global Payments (EGP) is looking for top engineering talent to help drive the development of our payment platform, seamlessly roll out new payment methods, and continuously improve on our operational excellence and engineering practices. We offer a highly dynamic set of services that enable customers worldwide to pay for travel in a variety of ways. We build, operate , and improve payment services for Expedia Group's brands, our suppliers (hoteliers, airlines, vacation rental owners/agencies, etc.), and our corporate needs. We do this accurately and at scale, processing over $100 billion payments in 55\+ currencies in over 155 countries every year, and across a diverse set of payment options! This opportunity presents great technical challenges and offers the potential to have a tremendous business impact.
Technology and innovation are at the heart of our organization. We provide solutions that reduce the cost of payments and improve performance, scalability , availability, and resiliency. We also provide an abundance of functional support to services in our platform, and the needs are ever\-growing, as we adapt to new payment solutions and capabilities.
This position focuses not only on implementing innovative software solutions for e\-commerce payment systems at scale but also on being a role model and mentor to your fellow engineers. You will get to expand your skills in building highly scalable solutions while influencing others and raising the bar on the overall level of excellence within the team. You will also get the opportunity to influence decisions across the technology ecosystem within Expedia Group by being a key domain guide. Additionally, your input will be critical to the selection of new senior\-level hires on the team.
Role Summary
Design and deliver real\-time, AI\-powered fraud and abuse defenses on a global scale. As a Software Development Engineer III, you will build and operate cloud\-native decisioning and automated remediation systems, help simplify our platform, and collaborate with cross\-functional teams to achieve measurable outcomes.
In this role you will:
- Con trib ute t o th e design and implementation of low\-latency risk decisioning (signals \+ rules \+ models) and automated remediation, owning the quality and reliability of the services and components you build.
- Apply AI\-assisted SDLC practices end to end: AI\-accelerated design and code generation, prompt and context management for coding agents, human\-in\-the\-loop review of AI\-generated code, automated test generation, and CI/CD guardrails.
- Build, deploy, and operate agentic workflows and multi\- agent systems — decomposing tasks, orchestrating tools and function calls, managing memory, and embedding human\-in\- the\-loop controls — to automate and reimagine manual operational processes, not just augment them.
- Help simplify and modernize the platform (streaming/data pipelines, microservices, CI/CD, con figuration\-driven con trols) so that teams can iterate quickly and safely.
- Implement and maintain SLOs, observability, and safety/rollback mechanisms for the services you own, ensuring security, privacy, and compliance requirements are met by design.
- Participate in evaluating vendors and in\-house solutions for performance, cost, and risk posture, contributing data and implementation perspectives into the decision process.
- Collaborate closely with engineering, product, operations, security, and compliance teams to deliver outcomes, sharing knowledge with peers and supporting a high bar for engineering excellence.
- Mentor other engineers and champion the use of AI within the organization
Minimum Qualifications
- Bachelor’s degree in Computer Science or a related technical field; or equivalent related professional experience.
- 5\+ years of software engineering, with significant experience building and operating high\-scale production backend services, including shipping Gen AI and agentic systems to production.
- Hands\-on proficiency in at least one modern programming language and core software engineering practices, including system design (LLD), API design, and data modeling for AI\-enabled services.
- Familiarity with distributed cloud\-native engineering at scale (AWS, GCP, or Azure), microservices, API\-driven design, SQL/NoSQL databases, and data streaming/processing (Kafka, Flink, Spark).
- Hands\-on experience using AI coding assistants and agents (e.g., Claude Code, Cursor, GitHub Copilot, or equivalent) to ship production software faster — applying AI\- assisted SDLC practices across design, implementation, reviews, and test generation, with strong prompt/context management and human\-in\-the\-loop review of AI\-generated code.
- Experience building, monitoring, and debugging LLM and multi\-agent applications, with frameworks and platforms such as LangChain , LangGraph , Langfuse , or equivalent.
- RAG\-based architecture experience, including data orchestration frameworks such as LlamaIndex , vector databases such as Pine con e, or equivalent.
- Exposure to various LLM providers such as OpenAI, Gemini, and Anthropic.
Preferred Qualifications:
- Track record automating and reimagining manual operational processes with agentic systems, reducing manual operations through automation and platform simplification.
- Experience building and integrating applications with AI/ML solutions or LLM models, including model API consumption, RAG patterns, agentic orchestration, and connecting AI\-driven outputs to scalable backend services with observability and cost\-awareness.
- Graph/sequence modeling or entity resolution at scale; device and behavioral signals.
- Experience with cloud cost/performance tuning and capacity planning.
- Marketplace, travel, or e\-commerce experience.
Please note that this role is only available in Austin, TX , in alignment with our flexible work model, which requires employees to be in\-office at least three days a week. We are unable to offer relocation assistance for this role.
The total cash range for this position in Austin is $146,000\.00 to $204,500\.00\. Employees in this role have the potential to increase their pay up to $233,500\.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 https://careers.expediagroup.com/life .
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 https://expedia.service\-now.com/askeg?id\=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 https://careers.expediagroup.com/jobs/ .
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.
Salary Context
This $146K-$233K range is above the median for AI Product Manager roles in our dataset (median: $188K across 140 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 3,708 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Expedia Group, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $216,175 based on 270 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($189K) sits 12% below the category median. Disclosed range: $146K to $233K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Expedia Group AI Hiring
Expedia Group has 6 open AI roles right now. They're hiring across Data Scientist, AI/ML Engineer, AI Product Manager. Positions span Seattle, WA, US, Austin, TX, US, San Jose, CA, US. Compensation range: $196K - $299K.
Location Context
AI roles in Austin pay a median of $214,343 across 87 tracked positions.
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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