Director, Engineering - Personalization & Recommendations

Company Overview

Fox Corporation encompasses prominent brands such as FOX News Media, FOX Sports, FOX Entertainment, FOX Television Stations, and Tubi Media Group, united by pioneering technology, data-driven insights, and compelling content to shape digital entertainment's future. Their direct-to-consumer platforms provide personalized, scalable experiences to millions globally.

Role Summary

As the Director of Engineering for Personalization & Recommendations (PNR), you will spearhead the engineering teams creating large-scale platforms that personalize content and recommendations across FOX's digital offerings. This role entails setting engineering strategies, nurturing high-performing teams, and enforcing technical excellence in a vital segment of FOX's product ecosystem.

Responsibilities

• Lead and expand multiple engineering squads focusing on personalization and recommendation platforms for FOX's digital products.
• Develop and implement engineering strategies and technology roadmaps aligned with FOX’s vision.
• Make architectural decisions ensuring highly scalable, resilient, and low-latency services for recommendations and personalization.
• Cultivate a culture of engineering excellence, innovation, responsibility, collaboration, and ongoing improvement.
• Collaborate extensively with Product, Data Science, Machine Learning, Analytics, Platform Engineering, and DevOps teams to drive key business initiatives.
• Set engineering standards including software architecture, coding, testing, CI/CD, observability, security, and operational best practices.
• Oversee organizational development activities such as hiring, talent nurturing, succession planning, performance evaluations, and team growth.
• Mentor Engineering Managers and senior technical staff to build future leaders.
• Enhance engineering workflows, release processes, platform reliability, and developer efficiency.
• Balance timely feature delivery with long-term scalability, modernization, and technical debt management.
• Lead creation of experimentation platforms including A/B testing tools supporting data-informed decision-making.
• Ensure recommendation services achieve high availability, scalability, performance, and measurable business impact.
• Work with cross-functional teams to integrate services across Web, Mobile, and Connected TV platforms.
• Effectively communicate engineering direction, progress, risks, trade-offs, and business outcomes to executives.
• Foster an inclusive culture emphasizing ownership, innovation, customer experience, and continuous learning.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or similar technical discipline.
• Minimum 12 years of software engineering experience with at least 5 years in leadership of multiple engineering teams or units.
• Proven expertise building scalable backend and distributed systems serving millions of users.
• Experience developing personalization, recommendation, user engagement, search, or content discovery platforms.
• Collaborated with Machine Learning and Data Science teams to deploy ML models into production environments.
• Strong grasp of distributed systems, microservices, event-driven architecture, APIs, and cloud-native applications.
• Skilled in designing and operating scalable services on AWS or equivalent cloud infrastructure.
• Experienced in leading Engineering Managers, Staff Engineers, and senior technical leaders in AI/ML domains.
• Familiarity with Agile methodologies, DevOps practices, CI/CD pipelines, observability, and operational engineering excellence.
• Successful track record managing organizational growth, recruitment, employee development, performance reviews, and succession planning.
• Business savvy with ability to align engineering goals with product strategy and customer needs.
• Exceptional communication, stakeholder engagement, and presentation skills for executive-level interactions.

Preferred Qualifications

• Hands-on experience building recommendation engines, personalization platforms, customer segmentation, or content ranking systems.
• Knowledge of experimentation platforms, feature flagging, and A/B testing frameworks.
• Familiarity with ML lifecycle tools, feature stores, and real-time predictions.
• Background in streaming services, digital media, or consumer-facing applications.
• Understanding of data platforms, analytics pipelines, and customer behavior modeling.
• Experience with observability tools such as Datadog, Grafana, New Relic, or Splunk.
• Proven history of leading globally distributed engineering teams.

Equal Opportunity Statement

Fox Corporation is committed to equal employment opportunity without discrimination based on race, religion, sex, national origin, gender identity, disability, veteran status, or other legally protected categories. Qualifications with criminal history consistent with applicable laws are also considered.