Job description

For over four decades, Cirrus Logic has been propelled by the top engineers in mixed-signal processing. Our rockstar team thrives on solving complex challenges with innovative end-user solutions for the world's top consumer brands. Cirrus Logic is also known for its award-winning culture, which was built on a foundation of inclusion and fairness, meaningful community engagement, and delivering enjoyable employee experiences at every turn. But we couldn’t do it without our extraordinary workforce – and that’s where you come in. Join our team and help us continue to make Cirrus Logic an exceptional place to grow your career! We’re looking for a Senior Validation Software Engineer to develop and support the software that enables silicon validation. In this hands-on role, you’ll build shared Python tools, improve automated test infrastructure, and help engineers collect, analyze, and trust their validation results. Applying AI will be a central part of your work. You’ll partner closely with our AI Applications team to integrate AI-assisted development and agent workflows into validation engineering—from diagnosing test failures and supporting releases to automating characterization and improving data quality. You’ll bring the software and validation context needed to turn shared AI capabilities into reliable tools for everyday engineering work. What You'll Do •Develop and maintain shared Python packages, test frameworks, and applications used across silicon validation projects. • Apply AI-assisted development tools to implementation, testing, code review, and documentation, taking responsibility for the quality of delivered software. • Work with the AI Applications team to build validation-specific agent workflows that use engineering tools, project documentation, test records, and measurement data. • Improve build and test infrastructure, diagnose worker and station failures, and follow support issues through verified resolution. •Coordinate software releases, check dependencies and compatibility, and maintain deployment and recovery procedures. •Develop reusable test interfaces and workflows that allow teams to share tests across validation platforms. •Automate characterization workflows, connecting requests for missing data with test execution, capture, quality checks, and publication. •Improve logging, run history, and traceability so engineers can investigate failures and reproduce results. •Evaluate AI-enabled workflows against representative engineering tasks, checking correctness, failure handling, and practical benefit. •Document operating procedures, demonstrate improvements, gather user feedback, and mentor engineers. Required Skills and Qualifications •BS in Computer Science, Electrical Engineering, Computer Engineering, or a related field, with 5+ years of relevant industry experience. •Strong Python skills and experience developing and supporting shared software libraries, frameworks, or engineering tools. •Demonstrated ability to deliver substantial hands-on software work independently within a small team, including defining tasks, setting priorities, resolving technical problems, and carrying solutions through deployment and support. •Experience with automated testing, Git, code review, continuous integration, and software release practices. •Experience integrating software with test equipment, hardware systems, or engineering infrastructure. •Practical experience using AI coding tools or integrating LLM-based capabilities into software workflows, with the ability to verify outputs and diagnose failures. •Effective debugging skills across software components, dependencies, and operating environments. •Ability to translate engineering needs into scoped improvements and carry work through implementation, deployment, and support. •Clear technical communication and documentation skills, with experience collaborating across software and hardware teams. Preferred Skills and Qualifications •Experience in silicon validation, characterization, lab automation, or hardware-in-the-loop testing. •Experience connecting AI agents to APIs, engineering tools, or technical knowledge sources. •Experience testing AI-enabled workflows for accuracy, repeatability, and recovery from unsuccessful actions. •Familiarity with Jenkins, distributed build workers, and Windows or Linux environments. •Experience with lab instrumentation, instrument drivers, or device communication protocols. •Experience developing data pipelines, database-backed applications, or engineering dashboards. •Familiarity with measurement provenance, data quality checks, and reproducible test execution. •Experience maintaining compatibility across projects and helping engineering teams adopt shared tools. Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time. Export control restrictions based upon applicable laws and regulations would prohibit candidates who are nationals of certain embargoed countries from working in this position without Cirrus Logic first obtaining an export license. Candidates for this role must be able to access technical data without a requirement for an export license. We are unable to sponsor or obtain export licenses for this role. Cirrus Logic strives to select the best qualified applicant for any opening. Different approaches, ideas and points of view are both valued and respected. Employment decisions are made on the basis of job-related criteria without regard to race, color, religion, sex, national origin, age, protected veteran or disabled status, genetic information, or any other classification protected by applicable law.

Requirements

Must-haves

Develop and maintain shared Python packages, test frameworks, and applications used across silicon validation projects.
Apply AI-assisted development tools to implementation, testing, code review, and documentation, taking responsibility for the quality of delivered software.
Work with the AI Applications team to build validation-specific agent workflows that use engineering tools, project documentation, test records, and measurement data.
Improve build and test infrastructure, diagnose worker and station failures, and follow support issues through verified resolution.
Coordinate software releases, check dependencies and compatibility, and maintain deployment and recovery procedures.
Develop reusable test interfaces and workflows that allow teams to share tests across validation platforms.
Automate characterization workflows, connecting requests for missing data with test execution, capture, quality checks, and publication.
Improve logging, run history, and traceability so engineers can investigate failures and reproduce results.
Evaluate AI-enabled workflows against representative engineering tasks, checking correctness, failure handling, and practical benefit.
Document operating procedures, demonstrate improvements, gather user feedback, and mentor engineers.
Required Skills and Qualifications
BS in Computer Science, Electrical Engineering, Computer Engineering, or a related field, with 5+ years of relevant industry experience.
Strong Python skills and experience developing and supporting shared software libraries, frameworks, or engineering tools.
Experience with automated testing, Git, code review, continuous integration, and software release practices.
Experience integrating software with test equipment, hardware systems, or engineering infrastructure.
Practical experience using AI coding tools or integrating LLM-based capabilities into software workflows, with the ability to verify outputs and diagnose failures.
Effective debugging skills across software components, dependencies, and operating environments.
Ability to translate engineering needs into scoped improvements and carry work through implementation, deployment, and support.
Clear technical communication and documentation skills, with experience collaborating across software and hardware teams.
Experience in silicon validation, characterization, lab automation, or hardware-in-the-loop testing.
Experience connecting AI agents to APIs, engineering tools, or technical knowledge sources.
Experience testing AI-enabled workflows for accuracy, repeatability, and recovery from unsuccessful actions.
Familiarity with Jenkins, distributed build workers, and Windows or Linux environments.

Nice-to-haves

Preferred Skills and Qualifications

Application prep

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Keywords to mirror

pythonaillm

Platform: lever
Effort: quick