Principal Software Development Engineer - Business to Agent

Skills covered in University

About the role

Expedia Group is entering an era where AI agents become a primary interface between travelers and brands, and is extending that foundation into a dedicated marketing capability. Set the technical vision and own the target architecture for the agentic marketing platform, building the systems that make Expedia Group's supply, pricing, and brand legible, accessible, and preferred by horizontal agents, agent browsers, and emerging agent surfaces.

What you'll do

• Set technical vision for agentic marketing: lead the technical vision and own the target architecture for the agentic marketing platform, spanning data, services, workflows, experimentation, third-party APIs, and agent-facing surfaces, partnering closely with the agentic search lead who owns channel strategy and outcomes.
• Translate the agentic search strategy and investment roadmap into a sequenced, opinionated engineering plan with clear trade-offs and success criteria, and partner with product, marketing, data science, SEO/AEO, and architecture leaders to align on priorities, interfaces, and ownership boundaries.
• Build agent legibility and access: design and ship systems that make Expedia Group content reliably machine-readable and preferred across different agent archetypes, including horizontal agents, agentic commerce, browsers, and co-workers.
• Extend marketing surfaces beyond traditional web indices into agent-specific indices, model training data, live retrieval, and memory infrastructure, and create products designed for specific agent archetypes and crawlers, including agent-specific surfaces, indices, and CLIs.
• Build 0-to-1 by standing up the first measurement, agent-observability, data and content, and agent-specific products, and ensure high-quality agent access via APIs, MCPs, feeds, and other integration points, including authorization, observability, and SLOs.
• Lead the design of observability and experimentation to understand how agents reason, covering chain-of-thought logging, ranking signals, and bias analysis.
• Architect engineering workflows around fleets of autonomous coding agents and sub-agents, treating orchestration of agent labor, not just personal output, as the core leverage model.
• Work cross-functionally with many internal and external teams to deliver outcomes, with proven ability to influence without direct authority.
• Serve as the technical anchor for a small, ring-fenced squad of engineers, setting engineering standards, reviewing designs, and making crisp architectural calls while working closely with the broader engineering team, and coach and mentor engineers across Marketing Tech and adjacent orgs, raising the bar on system design, AI integration, experimentation, and operational excellence.
• Foster an AI-native, zero-coordination-tax culture that uses automation and agents to amplify output and move quickly, with failure as a design principle, and keep systems observable, resilient, secure, and cost-efficient with clear SLOs and runbooks.
• Operate with a highly discretionary build budget, covering pre-approved token consumption, AI vendor adoption, and unconventional experimentation such as dedicated hardware for synthetic agent-log generation, and spend it to maximize speed.

What we're looking for

• 10+ years of hands-on software engineering experience, or 6+ years with a Master's degree.
• Hands-on experience with agentic and AI systems, including LLMs, RAG, tools and MCPs, and agent orchestration.
• Demonstrated expertise in systems architecture, API design, and integrating third-party products and platforms.
• Product sense: the ability to reason about what to build and for whom, prioritize on desirability, feasibility, and viability, and partner with product as a peer.
• Strong proficiency in at least one modern backend language such as Java, Kotlin, Go, Python, or Scala, and comfort working across services, data, and infrastructure.
• Strong experience with cloud platforms, AWS preferred, and container orchestration with Kubernetes, plus modern CI/CD and observability tooling.
• Solid understanding of data modelling, streaming and batch processing, and experimentation frameworks.
• Has architected scalable, high-traffic services that translate a product vision into an end-to-end technical system.
• Practical experience with AI developer tools such as Claude, GitHub Copilot, Cursor, Codex, or Kiro, including evaluating adoption, usage depth, and impact on developer workflows and outcomes.
• Strong cross-functional collaboration skills: able to partner with marketing, product, data science, architecture, and legal to make high-quality trade-offs.
• Experience mentoring senior engineers, building healthy engineering cultures, and influencing without formal authority.
• Bonus: experience with marketing technology, ad platforms, or growth and optimization stacks; active immersion in the AI ecosystem, with relationships with frontier labs, agent platforms, or AI-native startups treated as a meaningful signal of genuine engagement, not just familiarity; and familiarity with AI/ML in production, including model integration patterns, evaluation, and safety guardrails.
• Bonus: comfort operating in pre-playbook spaces where hypotheses will be wrong, experiments will fail, and rapid iteration is required; and proven ability to translate ambiguous strategy into executable technical roadmaps, balancing near-term delivery with long-term architecture.

Posted

1 hour ago · Aug 13, 2026