Software Development Engineer Test, Backend

OVERVIEW OF THE COMPANY

Fox Corporation is home to industry-leading brands including FOX News Media, FOX Sports, FOX Entertainment, FOX Television Stations, Tubi Media Group, and FOX One, our recently launched direct-to-consumer (DTC) platform.
Across our portfolio, we build and operate large-scale digital platforms that serve millions of users globally. Our teams combine innovative technology, deep data insights, and world-class content to deliver highly personalized, reliable, and scalable consumer experiences across web, mobile, and connected TV platforms.

As an SDET (Software Development Engineer in Test) working on backend systems for API, Personalization & Recommendations (PNR), or Search, you will own backend quality end-to-end across highly distributed, ML-powered systems.
While this is a QA-focused role, it demands strong software engineering skills to build scalable automation, validation frameworks, and quality systems for complex backend and ML-powered platforms.
This is not a manual QA role. The focus is on automation, systems thinking, and quality engineering at scale. You will define test strategies for complex service interactions, build and scale backend automation, and ensure release confidence for high-traffic, production-critical systems.
You will work closely with Backend Engineers, Platform teams, Data Scientists, and ML Engineers to ensure correctness, reliability, and early detection of issues, well before they impact users.
This role requires strong quality engineers who take end-to-end ownership of backend quality, can work independently with minimal guidance, and consistently uphold a high bar for correctness, reliability, and engineering rigor in test and automation.

• Own backend quality end-to-end, including test strategy, automation, and release confidence.

• Design, build, and maintain robust automation frameworks for API, service, data, and workflow validation.

• Build scalable, reusable backend automation and regression suites, not one-off scripts.

• Validate synchronous and asynchronous flows across distributed microservices.

• Validate data persistence, caching behavior, and consistency across services.

• Perform service virtualization and dependency mocking where required.

• Validate personalization and recommendation workflows as backend capabilities.

• Verify correctness of inputs, outputs, and decisioning logic for ML-driven services.

• Validate model inference pipelines, including online and batch inference.

• Partner with Data Scientists and ML Engineers to understand expected behavior, metrics, and edge cases.

• Validate data quality, transformations, and feature correctness feeding downstream ML systems.

• Support validation of ML concepts such as features, training vs inference, evaluation metrics, drift, and bias.

• Validate advanced search systems, including semantic and vector-based search.

• Validate search relevance, ranking correctness, and query understanding pipelines.

• Validate systems supporting NER, intent detection, query classification, and query rewriting.

• Validate LLM-powered and conversational search experiences, including multi-turn and agentic flows.

• Perform scenario-based validation of search and recommendation decisioning logic.

• Execute and support performance, scalability, and reliability testing for backend services.

• Build monitoring and validation pipelines that detect issues early and proactively.

• Integrate automation into CI/CD pipelines to ensure consistent quality gates.

• Partner with engineering teams to continuously improve testability, observability, and system resilience.

• Bachelor’s or Master’s degree in Computer Science or a related technical field.

• 3–7 years of experience as an SDET or Automation Engineer with a strong backend focus.

• Strong software engineering and automation skills using Python or Java.

• Solid understanding of distributed systems, microservices, and event-driven architectures.

• Experience validating APIs, services, data pipelines, and complex backend workflows.

• Experience testing personalization, recommendation, or search platforms.

• Practical experience validating AI/ML-powered systems in production environments.

• Working knowledge of ML concepts, including features, training vs inference, evaluation metrics, drift, and bias.

• Experience validating data pipelines built on platforms such as Spark, Databricks, Kafka, or similar.

• Strong SQL skills for large-scale data validation.

• Experience with CI/CD systems and Git-based workflows.

• Exposure to cloud platforms such as AWS, GCP, or Azure.

• Strong debugging, analytical, and communication skills.

• Ability to take ownership of backend quality and drive results with minimal guidance.

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We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, gender identity, disability, protected veteran status, or any other characteristic protected by law. We will consider for employment qualified applicants with criminal histories consistent with applicable law.