Senior AI Engineer

Cirrus Logic
Austin, TX, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Computer Engineering Software Debugging DevOps Firmware Hardware-In-The-Loop Simulation Python (Programming Language) Machine Learning Software Tools Software Systems Retrieval-Augmented Generation Large Language Models
+3 more
Model Validation Information Technology Automation Anywhere

Job description

Experteer Overview As Senior AI Engineer on Cirrus Logic’s centralized AI Core team, you will build and scale AI-enabled engineering capabilities across R&D hardware, software, and firmware. You’ll translate evolving AI tech into secure, reliable improvements for design, testing, debugging, and maintenance in hardware-adjacent environments. You’ll create repeatable AI workflows, integrate AI with engineering tools and hardware labs, and help define the AI roadmap for R&D. This role offers a chance to shape reusable AI core capabilities and drive measurable impact at scale. Compensation / Benefits * Identify and prototype high-value AI use cases with hardware, software, firmware, and DevOps leaders * Design and evaluate AI-assisted workflows for firmware/code development, debugging, and productivity * Implement retrieval-augmented generation, contextual knowledge, tool integration, and agentic workflows with internal data * Connect AI systems to engineering tools, repositories, build/test systems, docs, and hardware environments * Establish rigorous evaluation methods for quality, security, and hardware-in-the-loop validation * Transform pilots into reusable AI Core capabilities including architectures, libraries, and governance * Contribute to the AI roadmap, including build-vs-buy, data/access requirements, and deployment patterns * Collaborate with security, IT, legal, and leadership to ensure responsible use of models and data * Share learnings across the AI Core team and R&D through demonstrations and training * Create repeatable, validated AI usage patterns for Cirrus engineers in hardware-adjacent contexts Tasks * Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or related field * 5+ years of relevant experience in software/AI-ML systems, developer infrastructure, embedded systems, or related areas * Strong Python software engineering skills with production-quality tools or services * Experience applying modern AI/ML technologies (LLMs, retrieval-augmented generation, embeddings, tool calling, agents, model evaluation) * Experience designing reliable software systems with clear interfaces, observability, testing, security, and maintainability * Ability to move from ambiguous problem statements to prototypes and adoption * Capacity to work across software, firmware, hardware, test, DevOps, IT, and security teams * Strong technical judgment and ability to explain AI tradeoffs to technical and leadership audiences Key requirements *

Requirements

AI systems, docs, and hardware environments * Establish rigorous evaluation methods for quality, security, and hardware-in-the-loop validation * Transform pilots into reusable AI Core capabilities including architectures, libraries, and governance * Contribute to the AI roadmap, including build-vs-buy, data/access requirements, and deployment patterns * Collaborate with security, IT, legal, and leadership to ensure responsible use of models and data * Share learnings across the AI Core team and R&D through demonstrations and training * Create repeatable, validated AI usage patterns for Cirrus engineers in hardware-adjacent contexts Tasks * Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or related field * 5+ years of relevant experience in software/AI-ML systems, developer infrastructure, embedded systems, or related areas * Strong Python software engineering skills with production-quality tools or services * Experience applying modern AI/ML aaaaaaaaaal _ (LLMs, retrieval-augmented generation, embeddings, tool calling, agents, model evaluation) * Experience designing reliable software systems with clear interfaces, observability, testing, security, and maintainability * Ability to move from ambiguous problem statements to prototypes and adoption * Capacity to work across software, firmware, hardware, test, DevOps, IT, and security teams * Strong technical judgment and ability to explain AI tradeoffs to technical and leadership audiences Key requirements *

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