Software Engineer (Java) in Test

Software Engineer (Java) in Test Paramount Skydance Corp. is seeking a Software Engineer in Test to design, architect, and deliver high-quality, scalable, and reliable automated testing solutions across our enterprise platforms. This role requires robust Java engineering skills and knowledge of advanced test automation. It also needs experience in the media and streaming domain. The goal is to improve quality, reduce risk, and provide top-notch customer experiences on CTV, SmartTV, mobile, and web platforms. As a member of the Global Quality Engineering (GQE) organization, you will utilize our existing departmental automation framework to create and maintain automated tests across a variety of front-end clients and back-end services. You will also leverage AI-augmented development and testing practices using tools such as GitHub Copilot (in-IDE), Cursor, and similar tools. Key Responsibilities Create Robust & Reliable Automation Coverage across front-end and back-end Create and maintain automated tests using our existing Java-based departmental test automation framework supporting API, UI, Mobile, CTV/SmartTV, and integration testing; introduce reusable libraries, utilities, and patterns to improve stability and scale. Utilize scalable patterns for reusable test components, data management, assertions, parallelization, and distributed execution. Integrate the framework deeply into CI/CD pipelines to support shift-left testing and continuous quality. AI-Augmented Quality Engineering Champion AI-assisted development and testing using tools such as GitHub Copilot (IDE), Cursor, and LLM-based assistants to improve developer productivity, test authoring velocity, code reviews, and defect triage. Apply prompt engineering and retrieval techniques to accelerate test case generation, log/telemetry summarization, video-quality anomaly detection, and root-cause analysis. Evaluate and integrate useful AI capabilities that measurably reduce flakiness, false positives, and triage time within the existing framework. Media & Multi-Platform Quality Expand automation coverage for video playback, streaming resiliency, DRM flows, SSAI/CSAI ad insertion, captions/subtitles, and content protection. Validate QoE metrics (startup time, rebuffering ratio, frame drops, video/audio sync, error recovery) across Roku, Fire TV, Android TV/Google TV, Samsung Tizen, LG webOS, Apple TV, iOS/Android mobile apps, and modern web players. Leverage media tooling such as ffmpeg/ffprobe, Charles/Fiddler, and player inspection APIs for diagnostics and validation. Ensure consistent adoption of engineering best practices, coding standards, and high-quality test development patterns. Technical Execution Design and implement complex automated test suites using Java, Selenium, Appium, JMeter, Locust, REST-Assured, TestNG/JUnit, and related tooling within the existing framework. Build and optimize testing strategies including API/contract, integration, performance/reliability, and device-level testing for CTV/SmartTV, mobile, and web. Diagnose and tackle issues related to automation reliability, environment instability, device fragmentation, and system integration. Required Qualifications 3+ years of experience in software engineering or quality engineering with robust Java development expertise. Demonstrated experience using and enhancing an existing enterprise/departmental automation framework (not building entirely new frameworks). Deep expertise in common test automation tools (Selenium, Appium, Playwright, REST-Assured, TestNG, JUnit, Maven/Gradle). AI experience (must-have): hands-on use of AI-assisted development tools such as Claude Code, GitHub Copilot (IDE), Cursor or similar. Solid knowledge of software design patterns, data structures, and core engineering principles. Preferred Qualifications Familiarity with observability and APM tools (Grafana, Prometheus, NewRelic, DataDog) and media telemetry(Conviva, MUX, NPAW etc). Experience with contract testing (PACT), service virtualization, or synthetic media test data. Exposure to CTV/SmartTV automation stacks and remote device labs. Key Competencies Quality mindset – commitment to reliability, maintainability, and continuous improvement. AI fluency – practical judgment on where AI adds measurable value in testing. Success Metrics Increased automation coverage across CTV/SmartTV, mobile, and web; reduced manual regression. Measurable reduction in escaped defects and media playback incidents. Improved stability and reliability of automated pipelines and device runs.