Director, Engineering – Personalization & Recommendations API (PNR)

Overview

Lead the engineering organization responsible for building scalable personalization and recommendation platforms that power content discovery and individualized user experiences across FOX's digital products.

What you'll do

• Lead and grow multiple engineering teams responsible for Personalization and Recommendation platforms across FOX's Digital Product ecosystem.
• Define and execute the engineering strategy and technology roadmap aligned with FOX's Digital Product vision.
• Drive architecture decisions for highly scalable, resilient, and low-latency recommendation and personalization services.
• Build a culture focused on engineering excellence, innovation, accountability, collaboration, and continuous improvement.
• Partner closely with Product Management, Data Science, Machine Learning, Analytics, Platform Engineering, and DevOps teams to deliver strategic business initiatives.
• Establish engineering best practices around software architecture, coding standards, testing, CI/CD, observability, security, and operational excellence.
• Lead organizational planning including hiring, talent development, succession planning, performance management, and team growth.
• Mentor Engineering Managers and Senior Engineers while building future technical leaders within the organization.
• Drive continuous improvements in engineering processes, release management, platform reliability, and developer productivity.
• Balance feature delivery with long-term platform scalability, modernization, and technical debt reduction.
• Lead the development of experimentation platforms including A/B testing capabilities to support data-driven product decisions.
• Ensure recommendation services deliver high availability, scalability, performance, and measurable business impact.
• Collaborate with cross-functional teams to integrate recommendation services across Web, Mobile, and Connected TV applications.
• Communicate engineering strategy, delivery status, risks, trade-offs, and business outcomes to executive leadership.
• Foster an inclusive engineering culture focused on ownership, innovation, customer experience, and continuous learning.

What you'll need

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• 12+ years of software engineering experience, including 5+ years leading multiple engineering teams or organizations.
• Proven experience building scalable backend platforms and distributed systems serving millions of users.
• Strong experience developing personalization, recommendation, customer engagement, search, or content discovery platforms.
• Experience working with Machine Learning Engineers and Data Science teams to productionize ML models.
• Strong understanding of distributed systems, microservices, event-driven architectures, APIs, and cloud-native application development.
• Experience designing and operating highly scalable services on AWS or similar cloud platforms.
• Proven experience leading Engineering Managers, Staff Engineers, and Senior Technical Leaders in AI or ML area.
• Strong knowledge of Agile software development, DevOps, CI/CD, observability, and engineering operational excellence.
• Demonstrated success managing organizational growth, hiring, coaching, performance management, and succession planning.
• Strong business acumen with the ability to align engineering investments with product strategy and customer outcomes.
• Excellent communication, stakeholder management, and executive presentation skills.

Nice to have

• Experience building recommendation engines, personalization platforms, customer segmentation systems, or content ranking services.
• Experience with experimentation platforms, feature flagging, and A/B testing frameworks.
• Familiarity with Machine Learning lifecycle tools, feature stores, and real-time inference systems.
• Experience working with streaming platforms, digital media, or consumer-facing applications.
• Knowledge of data platforms, analytics pipelines, and customer behavior modeling.
• Experience with observability tools such as Datadog, Grafana, New Relic, or Splunk.
• Experience leading globally distributed engineering organizations.