Applied AI/Automation Engineer

Internal AI assistants for engineering and operations workflows

Automation tools that reduce manual effort in recurring tasks

Search and knowledge solutions that improve access to technical information

AI-enhanced developer productivity utilities

Evaluation dashboards and quality metrics for AI-based systems

Reusable frameworks and components for future AI projects

Bachelor’s degree in Computer Science, Software Engineering, Electrical Engineering, or related field, or equivalent practical experience

6+ years of professional software engineering experience, including building and deploying production software

Strong programming skills in one or more languages such as Python, JavaScript, TypeScript, Java, or C#

Comfortable working with source control (Git, SVN)

Hands-on experience designing and building AI-enabled applications using large language model APIs, AI application frameworks, enterprise AI platforms, or similar technologies

Experience integrating software with APIs, cloud services, enterprise data sources, data pipelines, and knowledge repositories

Experience with AI evaluation, measurement, monitoring, observability, or feedback practices

Working knowledge of AI governance, responsible AI, cybersecurity, data privacy, and access-control considerations

Strong written and verbal communication skills, with experience working directly with internal customers and cross-functional teams

Strong problem-solving skills, including the ability to define abstract problems, prioritize competing needs, and develop concise, actionable solutions in ambiguous and fast-moving environments

Prior experience in the semiconductor or high-tech industry

Demonstrated ability to move AI prototypes into production, including testing, deployment, monitoring, maintenance, and retirement of solutions that no longer provide value

Experience designing AI agents, multi-step workflows, tool integrations, human-in-the-loop controls, or agent security patterns

Experience building reusable AI frameworks, platform components, skills, or developer-enablement resources that help other engineers adopt AI

Experience optimizing AI systems for quality, latency, reliability, and cost through techniques such as model selection, routing, caching, batching, or context management

Experience implementing enterprise AI security practices, including service identity, scoped permissions, secrets management, auditability, data residency, or protection of confidential intellectual property

Experience with rigorous AI experimentation and evaluation, including test-set design, sampling, human quality review, inter-rater reliability, or measurement of user and business outcomes

Experience partnering with security, IT, governance, and business stakeholders to establish standards and gain adoption for AI solutions

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.