{"id":2060422,"url":"https://alion.io/job/cirrus-logic-applied-aiautomation-engineer","title":"Applied AI/Automation Engineer","company":{"id":449717,"name":"Cirrus Logic","domain":"cirrus.com","url":"https://alion.io/company/cirrus-logic","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"C","score":59,"open_postings":115,"ghost_share":0.687,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-14T06:34:16Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Austin, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":133000,"max_usd":253000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1124},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"C#","optional":false},{"name":"Git","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"JavaScript","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"TypeScript","optional":false}],"status":"live","first_seen_at":"2026-10-07T22:49:10Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-14T16:09:52Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":6},"description":"Our Customer Enablement organization defines semiconductor system requirements, develops technical documentation, and supports internal teams and customers in using our devices.\nWe are seeking an Applied AI/Automation Engineer to design, build, deploy, and support practical AI solutions that improve internal engineering workflows, automate repetitive tasks, and make technical information easier to find and use. This role will apply the latest AI techniques within scalable software solutions, helping move promising ideas from experimentation into reliable, maintainable tools that deliver measurable value. The role will involve designing solutions that are secure, measurable, maintainable, and useful in people’s daily work.\nThis role will also contribute to the development of documentation and information tools, scripts, and utilities. We eagerly pursue scripting, data modeling, and process automation to operate more efficiently in collaboration with work partner teams.\nThe ideal candidate combines strong software engineering skills with hands-on experience building AI-enabled applications.\nDepending on business priorities, initiatives may include:\nBuilding LLM-powered assistants and copilots\nCreating AI agents and tool-integrated workflows that connect to enterprise systems\nAutomating repetitive engineering and operational tasks\nApplying document intelligence, extraction, classification, and summarization\nDeveloping internal developer-productivity tools\nDesigning evaluation methods, quality metrics, monitoring, and feedback loops\nImproving prompts, workflows, context retrieval, model selection, performance, and cost\nEstablishing secure deployment patterns, access controls, and responsible AI practices\nSuccess 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.\nKey Responsibilities\nDesign, develop, and implement new tools, scripts and utilities to help other engineering teams operate more efficiently\nWrite clean, well-documented code with a focus on scalability, performance, and maintainability\nConduct unit and integration testing to ensure code quality and stability\nIdentify and prioritize high-value AI use cases aligned with business and engineering needs\nDesign, build, test, and deploy AI-enabled skills, agents and workflows\nIntegrate AI capabilities with internal data sources, developer tools, documentation platforms, and enterprise systems\nCreate evaluation methods to measure output quality, reliability, accuracy, usage, and user value\nPartners with Applied AI and Security to ensureImplement safeguards for security, privacy, access control, and responsible AI usage\nDocument how to use the tools, as well as architecture, design decisions, implementation patterns, and operational practices\nStay current on the evolving AI tool and model landscape and recommend pragmatic adoption strategies\nRequired Knowledge, Skills and Abilities\nBachelor’s degree in Computer Science, Software Engineering, Electrical Engineering, or related field, or equivalent practical experience\n6+ years of professional software engineering experience, including building and deploying production software\nStrong programming skills in one or more languages such as Python, JavaScript, TypeScript, Java, or C#\nComfortable working with source control (Git, SVN)\nHands-on experience designing and building AI-enabled applications using large language model APIs, AI application frameworks, enterprise AI platforms, or similar technologies\nExperience integrating software with APIs, cloud services, enterprise data sources, data pipelines, and knowledge repositories\nExperience with AI evaluation, measurement, monitoring, observability, or feedback practices\nWorking knowledge of AI governance, responsible AI, cybersecurity, data privacy, and access-control considerations\nStrong written and verbal communication skills, with experience working directly with internal customers and cross-functional teams\nStrong problem-solving skills, including the ability to define abstract problems, prioritize competing needs, and develop concise, actionable solutions in ambiguous and fast-moving environments\nPrior experience in the semiconductor or high-tech industry\nPreferred Knowledge, Skills and Abilities\nDemonstrated ability to move AI prototypes into production, including testing, deployment, monitoring, maintenance, and retirement of solutions that no longer provide value\nExperience designing AI agents, multi-step workflows, tool integrations, human-in-the-loop controls, or agent security patterns\nExperience building reusable AI frameworks, platform components, skills, or developer-enablement resources that help other engineers adopt AI\nExperience optimizing AI systems for quality, latency, reliability, and cost through techniques such as model selection, routing, caching, batching, or context management\nExperience implementing enterprise AI security practices, including service identity, scoped permissions, secrets management, audit-ability, data residency, or protection of confidential intellectual property\nExperience with rigorous AI experimentation and evaluation, including test-set design, sampling, human quality review, inter-rater reliability, or measurement of user and business outcomes","description_format":"text","description_chars":5362,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United 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