Job Details

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 (IDE), Cursor, and similar tools.

Key Responsibilities:

• Create Robust & Reliable Automation Coverage across front-end and back-end
• AI-Augmented Quality Engineering
• Media & Multi-Platform Quality
• Technical Execution

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.