Software Development Engineer, Backend (Java)

Overview

Build and operate scalable, resilient backend systems and APIs that power multiple consumer-facing platforms across Fox's brands, with end-to-end ownership from design through production operations.

What you'll do

• Design, build, and operate backend services and APIs that run at high scale with strict reliability and performance requirements.
• Take complete ownership of assigned problem areas, from requirements understanding and system design to production rollout and ongoing operations.
• Perform high-level and low-level system design, clearly articulating trade-offs and architectural decisions.
• Write high-quality, maintainable, and well-tested code across backend components.
• Build and evolve distributed systems that are resilient, fault-tolerant, and observable in production.
• Optimize existing systems for performance, latency, scalability, and cost.
• Apply strong problem-solving skills and data structures knowledge to design efficient, real-world solutions.
• Collaborate with cross-functional teams to deliver backend capabilities that support evolving product needs.
• Participate actively in code and design reviews, maintaining high engineering standards.
• Continuously improve system reliability, developer productivity, and engineering best practices within the team.

What you'll need

• Bachelor's or Master's degree in Computer Science or a related technical field.
• 4-8 years of experience building backend software systems in production environments.
• Strong programming skills in one or more backend languages, preferably Java.
• Solid understanding of data structures, algorithms, and their application in backend and distributed systems.
• Experience designing and building distributed systems with a focus on scalability, availability, and reliability.
• Hands-on experience working with cloud-based systems (e.g., AWS or equivalent).
• Experience working with databases and data stores (relational and/or NoSQL) and an understanding of data modeling and performance trade-offs.
• Practical understanding of modern AI systems, including large language models (LLMs), and how to integrate AI capabilities into backend software.
• Familiarity with using AI to build, enhance, or operate software systems (e.g., LLM-based APIs, prompt-driven workflows, automation, developer productivity).
• Ability to work independently, take ownership, and deliver systems end-to-end with minimal guidance.