Globalization Platform Engineer

As Expedia Group accelerates its AI-driven transformation and expands globally, the ability to deliver truly local, high-quality experiences at scale has become a core competitive advantage.

The Globalization Platform Lead is a critical technical leadership role that ensures globalization is not a downstream activity, but a platform capability embedded into product development from day one. This role focuses on designing, deploying and maintaining the architecture of AI-enabled localization workflows, machine translation pipelines, and developer tooling that make it easier for product teams to launch globally.

This is a highly hands-on role for someone who enjoys building platforms, collaborating across teams, and shaping how global products are delivered.

Core responsibilities and deliverables:

1. Globalization Platforms & Architecture

• Design and implement services and workflows that support machine translation, localization automation, and multilingual content delivery.
• Contribute to technical designs and architecture reviews for globalization systems, including internal and external systems
• Translate product requirements into maintainable, scalable solutions.
• Help define technical standards and best practices for “global-by-default” development.
• Participate in quarterly planning & prioritization cycles and drives execution of assigned globalization initiatives.

2. AI/ML enablement

• Build integrations between LLMs, MT engines, and internal systems using APIs.
• Run technical experiments to test new AI-powered workflows, notably using Agentic AI.
• Engineer prompts and automation pipelines for AI-assisted localization.
• Leverage NLP/NLU techniques to improve localization automation, translation quality evaluation, and multilingual content understanding across Expedia Group experiences.

3. Machine Translation and linguistic systems

• Develop Python and/or AI-based tooling for MT evaluation, terminology extraction, and LQA automation.
• Maintain and improve MT pipelines and linguistic asset repositories.
• Work with our Analytics partners on building dashboards and reports from MT and TMS data sources.
• Partner with linguists and vendors to operationalize technical improvements.

4. Cross-functional delivery

• Collaborate with Product, UX, ML, and Platform teams to embed globalization early in the development lifecycle.
• Support workflow automation and process improvements.
• Help define success metrics and track business impact.
• Contribute to documentation and knowledge sharing for globalization tooling.

Functional/Technical Skills:

Required Experience

• 4–7 years of professional experience
• Strong programming skills (Python, Java, JavaScript/TypeScript)
• REST APIs, testing tools
• Regex and string handling
• Solid knowledge of Unicode, ICU & CLDR
• Working knowledge of NLP and NLU concepts: tokenization, embeddings, classification, sequence labeling, semantic similarity, intent/entity extraction
• Experience building production services, scripts, or internal platforms.
• Experience working with CI/CD pipelines and cloud environments.

Globalization & AI

• Solid knowledge of i18n, localization systems, globalization platforms, NMT engines.
• Strong literacy of LLM-based systems and prompt engineering.
• Experience in multilingual systems and experimentation.
• Working knowledge of NLU/NLP concepts

Architecture & Operations

• Experience contributing to system designs and technical reviews.
• Awareness of observability, monitoring, and reliability practices.
• Ability to troubleshoot production issues.

Collaboration & Communication

• Clear written and verbal communication skills.
• Comfortable working with global partners.
• Inclusive, collaborative approach to problem-solving.

Values & Leadership Competencies:

Customer first & Ownership

• Builds systems with traveler experience and quality at the core.
• Uses data to understand how global customers interact with products.
• Owns technical deliverables end-to-end within assigned projects.
• Flags risks early and proposes creative and when applicable, AI-based solutions.

Data-driven

• Defines measurable success criteria for globalization initiatives (quality, speed, cost, reliability, adoption) before building.
• Uses instrumentation and experimentation to validate whether AI/MT workflows improve outcomes vs. existing approaches
• Builds feedback loops so production data informs model/tooling improvements (e.g., post-edit data, LQA outcomes, customer signals).
• Makes tradeoffs transparently (e.g., cost vs. quality, latency vs. coverage) using evidence, not opinions.
• Operationalizes metrics into dashboards/alerts that teams can use without manual analysis.

Bias for action

• Ships incrementally, learns from results, and iterates quickly.
• Prototypes new ideas before scaling them.
• Ability to simplify complex systems and deploy clear, scalable and maintainable architectures.
• Works effectively across disciplines and geographies.
• Communicates clearly with both technical and non-technical partners.

Learning & Growth mindset

• Stays current on AI + globalization trends: keeps up with developments in LLMs, MT/NMT, evaluation methods, prompt/agent patterns, terminology management, and content quality practices
• Demonstrates a repeatable approach to learning: read, experiment, measure, operationalize.
• Can articulate trade-offs and “why” behind decisions, not just “how.”
• Converts new ideas into reliable tooling, standards, and best practices adopted by product teams.
• Builds personal credibility across disciplines by speaking both engineering and localization/linguistic perspectives.