Applied AI/Automation Engineer

Cirrus Logic

. Design, develop, and implement AI and non-AI tools and utilities for engineering teams .

Posted 10/8/2026full-timeAustin • Texas • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing AI-enabled applications and tools, with a strong focus on software engineering best practices, including coding, testing, and deployment. Proficient in integrating AI capabilities with enterprise systems while ensuring security, privacy, and compliance.

Highest-signal resume keywords

AI Application DevelopmentPython ProgrammingAI Integration with APIsSoftware Engineering ExperienceAI Governance and Security

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonJavaScriptTypeScriptJavaC#AI Application FrameworksAPI IntegrationUnit TestingIntegration TestingAI Evaluation Practices

Soft Skills

Strong Communication SkillsProblem-Solving Skills

Tools & Technologies

GitSVNCloud ServicesEnterprise AI PlatformsLarge Language Model APIs

Industry Keywords

Semiconductor IndustryHigh-Tech IndustryData PrivacyCybersecurityResponsible AI

Tech Stack

Tools & technologies

CloudCyber SecurityJavaJavaScriptPythonSubversionTypeScript

About the role

Key responsibilities & impact

Design, develop, and implement AI and non-AI tools and utilities for engineering teams
Write clean, documented, scalable, performant, and maintainable code
Conduct unit and integration testing
Identify and prioritize high-value AI use cases
Design, build, test, and deploy AI-enabled applications and internal tools
Integrate AI capabilities with internal data sources, developer tools, documentation platforms, and enterprise systems
Design and manage AI agent lifecycles, including multi-step tool use, planning, handoff, rollback, and deprecation
Create evaluation methods for output quality, reliability, accuracy, usage, and user value
Implement security, privacy, access-control, and responsible AI safeguards in partnership with Applied AI and Security
Document tool usage, architecture, design decisions, implementation patterns, and operational practices
Stay current with AI tools and models and recommend pragmatic adoption strategies
Deliver internal AI assistants, automation tools, technical search and knowledge solutions, developer productivity utilities, evaluation dashboards, quality metrics, and reusable AI frameworks

Requirements

What you’ll need

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 defining abstract problems, prioritizing competing needs, and developing 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
Experience optimizing AI systems for quality, latency, reliability, and cost
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
Experience partnering with security, IT, governance, and business stakeholders
Applicants must be authorized to work for any employer in the U.S.
Candidates must be able to access technical data without requiring an export license

Benefits

Comp & perks

Cirrus Logic award-winning culture built on inclusion and fairness
Meaningful community engagement
Enjoyable employee experiences
Career growth opportunities