Senior Manager, Global Platform Engineering (Data & AI/ML Platform)

This role is eligible for our hybrid work model: Two days in-office.

Our Technology team is the backbone of our company: constantly creating, testing, learning and iterating to better meet the needs of our customers. If you thrive in a fast-paced, ideas-led environment, you’re in the right place.

Our Data & AI/ML Platform team powers Priceline’s most strategic capabilities — enabling every business unit, product team, and data practitioner to innovate faster with secure, scalable, and governed access to data, machine learning, and GenAI technologies. We build the platform foundations that make self-service development possible across the company, and we take pride in delivering solutions that are performant, reliable, and enterprise-ready.

If you thrive at the intersection of platform engineering, AI/ML enablement, and enterprise-scale distributed systems, this is the place to make an impact.

Why this job’s a big deal

As Priceline scales personalization, AI-driven optimization, and intelligent automation, a modern platform for data and AI/ML is mission-critical.
This role leads the global platform engineering function that enables:

• Self-service data engineering, MLOps, LLMOps, and GenAI workloads

• Democratized access to trusted data and models

• A unified platform experience that accelerates innovation across the company

You will define and execute the platform strategy that powers everything from real-time insights to production machine learning to next-generation agentic AI systems.

In this role, you will get to:

Platform Strategy & Architecture

• Define and execute the technical strategy for Priceline’s Data, AI/ML & GenAI Platform — integrating data pipelines, analytics systems, ML tooling, model governance, and vector/RAG infrastructure into a unified self-service ecosystem.

• Design platform capabilities that support modern development patterns (MLOps, LLMOps, Feature Stores, Experimentation, Data Quality, Observability, Security-by-Design, etc.).

• Establish standards, patterns, and reusable components that accelerate delivery across engineering, product, analytics, and data science teams.
   

Build & Operate a Global Self-Service Platform

• Lead globally distributed teams responsible for building, scaling, and operating platform services across data engineering, ML engineering, automation, and GenAI frameworks.

• Enable BUs and product teams to ingest, process, build, deploy, and monitor data and AI/ML workloads independently and securely.

• Deliver high-availability, low-latency platform capabilities leveraging technologies such as BigQuery, Dataflow, Pub/Sub, Kafka, Spark, Dataproc, Composer, Vertex AI, Arize, Datastax Astra, Feature Stores, and model gateways.
   

Scale AI/ML & GenAI Adoption

• Collaborate with ML Platform, Data Science, and Product teams to enable experimentation, model deployment, evaluation, and monitoring at scale.

• Build platform-centric capabilities for LLM development, RAG, agentic workflows, prompt management, feature pipelines, and automation patterns.

• Provide frameworks and guardrails that democratize access to AI/ML while reducing operational overhead and risk.
   

Operational Excellence & Developer Productivity

• Drive engineering excellence through automation, standardization, CI/CD best practices, FinOps optimization, and robust SLO/SLA frameworks.

• Proactively improve performance, reliability, scalability, and cost efficiency of all platform components.

• Foster a culture of metrics-driven execution, continuous improvement, and operational rigor.

Leadership & Collaboration

• Lead, mentor, and grow high-performing global engineering teams; build strong engineering leadership pipelines.

• Influence and partner with senior leaders across Data, FinTech, Marketing, Product, Security, and Enterprise Architecture.

• Translate complex platform strategies into clear business impact and measurable outcomes.

Who you are

• 10+ years in software/data engineering with 4+ years leading platform or infrastructure-focused teams (data platforms, ML platforms, cloud platform engineering, etc.).

• Deep expertise in large-scale data architecture, streaming systems, data modeling, and ML/GenAI platform technologies (GCP preferred).

• Proven track record in building self-service platforms for data engineering, MLOps, LLMOps, or AI/ML workloads.

• Hands-on experience with modern tools like BigQuery, Dataflow, Pub/Sub/Kafka, Spark/Dataproc, Composer, Vertex AI, Vector DBs, Feature Stores, and enterprise observability stacks.

• Strategic thinker who can define multi-year platform roadmaps while delivering incremental value.

• Exceptional collaborator who thrives in cross-functional environments and can influence without authority.

• Illustrated history of living the values necessary to Priceline: Customer, Innovation, Team, Accountability and Trust

• The Right Results, the Right Way is not just a motto at Priceline; it’s a way of life. Unquestionable integrity and ethics is essential

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