{"id":1621759,"url":"https://alion.io/job/cirrus-logic-senior-ai-engineer","title":"Senior AI 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":"2026-10-13T05:45:00Z"}},"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":136000,"max_usd":259000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1124},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"C++","optional":false},{"name":"CI/CD","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"Linux","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"RTOS","optional":false},{"name":"Tool Use","optional":false}],"status":"live","first_seen_at":"2026-08-11T21:29:02Z","employer_posted_date":"2026-08-11","last_verified_at":"2026-10-13T08:17:40Z","board_verified":true,"closed_at":null,"days_open":62,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":62},"description":"The Role\nWe are seeking a hands-on Senior AI Engineer to join Cirrus Logic’s centralized AI Core team. You will develop, prototype, validate, and scale AI-enabled engineering capabilities across R&D’s Hardware, Software & Firmware design teams.\nThis is a builder role for an engineer who can translate rapidly evolving AI technology into secure, reliable, and measurable improvements in how products are designed, tested, debugged, and maintained. In this role you will be combining modern AI and agentic workflows with Cirrus-specific product knowledge, codebases, engineering processes, test infrastructure, and real hardware.\nThis role is ideal for an engineer energized by solving ambiguous technical problems, validating solutions rigorously, and turning pilots into practical engineering leverage at scale.\nWhat You’ll Own & Create\nThis is not an AI demonstration role - this is where you build trustworthy engineering capabilities, establish effective validation methods, and help shape how R&D applies AI.\nYou will:\nPartner with Hardware, Software & Firmware leaders, architects, developers, test engineers, and DevOps to identify, prioritize, and rapidly prototype high-value AI use cases.\nBuild and evaluate AI-assisted workflows for firmware and driver development, code understanding, debugging, test creation, documentation, and engineering productivity.\nDesign and implement retrieval-augmented generation, contextual knowledge, tool integration, and agentic workflows that safely use approved internal engineering information.\nConnect AI systems to appropriate engineering tools, repositories, build and test systems, documentation, and, where appropriate, hardware and lab environments.\nEstablish rigorous evaluation methods for AI-enabled workflows, including quality, correctness, security, developer experience, productivity, and hardware-in-the-loop validation.\nConvert successful pilots into reusable AI Core capabilities, including reference architectures, libraries, integration patterns, governance controls, documentation, and enablement materials.\nHelp define the technical roadmap for AI in R&D, including build-versus-buy recommendations, vendor evaluation, data and access requirements, and deployment patterns.\nWork with security, IT, legal, and engineering leadership to ensure responsible use of models, code, confidential information, and internal tools.\nShare learnings across the AI Core team and R&D through demonstrations, technical guidance, and practical training that supports adoption.\nYou will not simply introduce AI tools - you will establish repeatable, validated ways for Cirrus engineers to use AI effectively in hardware-adjacent development environments.\nSkills You’ll Bring to the Team\nBachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline, with 5+ years of relevant experience in software, AI/ML systems, developer infrastructure, embedded systems, firmware, or a closely related field. Advanced degree or equivalent practical experience is valued.\nStrong Python software engineering skills, with experience delivering production-quality tools, services, or developer infrastructure.\nPractical experience applying modern AI/ML technologies, including large language models, retrieval-augmented generation, embeddings and vector search, tool calling, agents, model evaluation, or AI application platforms.\nExperience designing reliable software systems with clear interfaces, observability, testing, security, and maintainability.\nDemonstrated ability to move from an ambiguous problem statement through prototype, evaluation, and engineering adoption.\nAbility to work effectively across software, firmware, hardware, test, DevOps, IT, and security disciplines.\nStrong technical judgment, structured problem solving, and communication skills, including the ability to explain complex AI tradeoffs to technical and leadership audiences.\nPreferred Knowledge, Skills, and Experience\nExperience with embedded software, firmware, device drivers, RTOS or bare-metal development, hardware bring-up, or hardware/software co-debug.\nExperience integrating AI systems with source control, CI/CD, issue tracking, documentation systems, build systems, test automation, or laboratory equipment.\nExperience with hardware-in-the-loop, simulation, emulation, or automated validation environments.\nKnowledge of C/C++, Linux, developer tooling, code analysis, and secure software-development practices.\nExperience evaluating and deploying commercial AI products as well as building targeted custom extensions.\nFamiliarity with enterprise data governance, access controls, model safety, and intellectual-property considerations.\nExperience developing reusable technical platforms, standards, or enablement materials for a broad engineering 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