layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

LAYIQ - Applied AI/Automation Engineer at Cirrus Logic, Austin, TX

Building LLM-powered assistants and copilots
Creating AI agents and tool-integrated workflows that connect to enterprise systems
Automating repetitive engineering and operational tasks
Applying document intelligence, extraction, classification, and summarization
Developing internal developer-productivity tools
Designing evaluation methods, quality metrics, monitoring, and feedback loops
Improving prompts, workflows, context retrieval, model selection, performance, and cost
Establishing secure deployment patterns, access controls, and responsible AI practices
Success in this role means delivering AI capabilities that are useful, trusted, adopted, and sustainable in production while helping engineering teams use AI efficiently and effectively.
Key Responsibilities: Design, develop, and implement new tools, scripts and 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 skills, agents and workflows
Integrate AI capabilities with internal data sources, developer tools, documentation platforms, and enterprise systems
Create evaluation methods to measure output quality, reliability, accuracy, usage, and user value
Partners with Applied AI and Security to ensureImplement 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
Required Knowledge, Skills and Abilities: 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
Preferred Knowledge, Skills and Abilities: 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, audit-ability, 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
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.

Applied AI/Automation Engineer

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