Principal AI Platform Engineer — Agentic Marketing

Expedia

Seattle (WA)

On-site

USD 231,000 - 324,000

Full time

14 days+

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Benefits offered by this job

medical, dental, and vision coverage

paid time off

Employee Assistance Program

wellness and travel reimbursement

travel discounts

IATAN membership

Job summary

Expedia Group in Seattle is seeking a senior software engineer to lead agentic marketing platform initiatives, shaping architecture across data, services, and workflows. You will own the technical vision, collaborate with product, marketing, data science, and architecture, and mentor engineers to raise the bar on AI integration, observability, and operational excellence.

The role emphasizes building scalable, AI‑driven systems, ensuring reliable agent access via APIs, and delivering measurable

Qualifications

10+ years of hands‑on software engineering experience (or 6+ with a Master’s)
Hands‑on experience with agentic / AI systems (LLMs, RAG, tools/MCPs, agent orchestration)
Demonstrated expertise in systems architecture, API design, and integrating third‑party products and platforms
Product sense, ability to reason about what to build and for whom, prioritize on desirability / feasibility / viability, and partner with product as a peer
Strong proficiency in at least one modern backend language (e.g., Java, Kotlin, Go, Python, Scala) and comfort working across services, data, and infrastructure
Strong experience with cloud platforms (AWS preferred) and container orchestration (Kubernetes), plus modern CI/CD and observability tooling
Solid understanding of data modelling, streaming/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 (e.g., Claude, GitHub Copilot, Cursor, Codex, 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

Responsibilities

Set technical vision for agentic marketing and own the outcomes
Lead 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.
Partner with product, marketing, data science, SEO/AEO, and architecture leaders to align on priorities, interfaces, and ownership boundaries.
Work cross functionally with many internal and external teams to deliver outcomes with proven ability to influence without direct authority.
Build agent legibility & access Design and ship systems that make EG content, reliably machine‑readable and preferred for different agent archetypes (horizontal agents, agentic commerce, browsers, co‑workers).
Extend marketing surfaces beyond traditional web indices into agent‑specific indices, model training data, live retrieval, and memory infrastructure.
Create and evolve products designed for specific agent archetypes and crawlers - including agent‑specific surfaces, indices, and CLIs.
Build 0-to-1: stand up the first measurement, agent‑observability, data/content, and agent‑specific products (CLIs, indices, agents).
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.
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 (e.g., chain‑of‑thought logging, ranking signals, bias analysis).
Anchor a small and focused engineering squad Serve as the technical anchor for a small, ring‑fenced squad (STL + engineers), setting engineering standards, reviewing designs, and making crisp architectural calls while working closely with the broader engineering team.
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.
Ensure systems are observable, resilient, secure, and cost‑efficient, with clear SLOs and runbooks.
Operate with a highly discretionary build budget - pre‑approved token consumption, AI vendor adoption, and unconventional experimentation (e.g., dedicated hardware for synthetic agent-log generation) - and spend it to maximize speed.