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About the Role

Design, build, deploy, and support practical AI solutions to improve internal engineering workflows, automate repetitive tasks, and enhance the accessibility of technical information. This role applies the latest AI techniques within scalable software solutions, moving ideas from experimentation into reliable, maintainable tools that deliver measurable value. The role involves designing secure, measurable, maintainable, and useful solutions for daily work, and contributing to documentation and information tools.

Responsibilities

Design, develop, and implement new AI and non-AI tools/utilities to help other engineering teams operate more efficiently
Write clean, well-documented code with a focus on scalability, performance, and maintainability
Conduct unit and integration testing to ensure code quality and stability
Identify and prioritize high-value AI use cases aligned with business and engineering needs
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
Agent design and lifecycle (multi-step tool use, planning, handoff, rollback, deprecation)
Create evaluation methods to measure output quality, reliability, accuracy, usage, and user value
Partner with Applied AI and Security to implement safeguards for security, privacy, access control, and responsible AI usage
Document how to use the tools, as well as architecture, design decisions, implementation patterns, and operational practices
Stay current on the evolving AI tool and model landscape and recommend pragmatic adoption strategies

Requirements

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
Applicants must be authorized to work for ANY employer in the U.S.
Candidates must be able to access technical data without a requirement for an export license.

Skills

AI
Automation
Software Engineering
Large Language Models (LLMs)
API Integration
Cloud Services
Enterprise Data Sources
Data Pipelines
Knowledge Repositories
AI Evaluation
AI Measurement
AI Monitoring
AI Observability
AI Feedback Practices
AI Governance
Responsible AI
Cybersecurity
Data Privacy
Access Control
Python
JavaScript
TypeScript
Java
C#
Git
SVN
Scripting
Data Modeling
Process Automation
Document Intelligence
Extraction
Classification
Summarization
Prompt Engineering
Workflow Design
Context Retrieval
Model Selection
Performance Optimization
Cost Optimization
Secure Deployment Patterns
Access Controls
Responsible AI Practices
Agent Design
Multi-step Tool Use
Planning
Handoff
Rollback
Deprecation
Human-in-the-loop Controls
AI Security Patterns
Reusable AI Frameworks
Platform Components
Developer Enablement
Quality Metrics
Latency Optimization
Reliability Optimization
Caching
Batching
Service Identity
Scoped Permissions
Secrets Management
Auditability
Data Residency
Confidential Intellectual Property Protection
AI Experimentation
Test-set Design
Sampling
Human Quality Review
Inter-rater Reliability
User Outcome Measurement
Business Outcome Measurement

Experience Level

6+ years of professional software engineering experience

Education Level

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

About the Company

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.
Our Customer Enablement organization defines semiconductor system requirements, develops technical documentation, and supports internal teams and customers in using our devices.

Equal Opportunity

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.