Principal AI Workflow Engineer

Responsibilities

• Evaluate emerging AI technologies and define a firmware AI roadmap aligned to business priorities, engineering efficiency, and measurable impact.
• Prototype, validate, and scale AI tools and workflows for code generation, review, testing, bug triage, and documentation in firmware engineering.
• Design and deploy agentic AI, RAG systems, and domain-specific LLM pipelines using firmware knowledge and defect data.
• Build AI-assisted tooling across CI/CD, IDEs, and build systems to improve quality, reduce review time, and accelerate development cycles.
• Identify high-value AI use cases across the firmware lifecycle, including simulation, modeling, regression testing, coverage analysis, and validation automation.
• Serve as the firmware organization's AI technical leader, guiding architecture, defining best practices, coaching engineers, and driving AI upskilling.
• Partner across AI Platform, Security, Legal, IT, DevOps, and executive leadership to define success metrics and ensure secure, compliant AI adoption.
• Architect secure, scalable AI infrastructure and build external partnerships with vendors and research institutions to advance AI-driven firmware engineering.
• Minimum Requirements:
• 10+ years of software or embedded engineering experience, with deep expertise in C/C++ development for embedded systems, RTOS environments, or storage firmware.
• Demonstrated hands-on experience building, fine-tuning, deploying, or integrating large language models (LLMs) and agentic AI systems in production or near-production environments.
• Experience designing AI-assisted developer tooling (code generation, review automation, test synthesis) that integrates with existing CI/CD and engineering workflows.
• Deep understanding of firmware validation techniques including unit testing, integration testing, simulation frameworks, and hardware-in-the-loop (HIL) testing.
• Strong technical communication skills with the ability to influence senior engineering leaders and translate complex AI capabilities into pragmatic engineering strategies.

Requirements

• Background in storage technology, SSD firmware, NAND flash systems, or semiconductor engineering environments.
• Experience with MLOps platforms and AI infrastructure (e.g., model serving, evaluation pipelines, vector databases, LLM gateways).
• Familiarity with AI-driven EDA tools, hardware design automation, or silicon lifecycle engineering.
• Contributions to open-source AI or firmware engineering projects, or publications in relevant technical communities.
• Experience with advanced prompt engineering patterns, multi-agent system design, or LLM-based software engineering research (SWE-bench, etc.).
• The compensation range for this role is $196,240 - $314,000. Actual compensation is influenced by a variety of factors including but not limited to skills, experience, qualifications, and geographic location.
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Benefits

Additional Information

The Principal Engineer, AI Transformation is a senior technical leader and individual contributor embedded within Solidigm's Firmware Organization. This role serves as the technical right-hand to the Head of AI Transformation, responsible for evaluating emerging AI technologies, designing practical adoption strategies, and leading the end-to-end integration of AI capabilities into firmware engineering workflows. The ideal candidate brings deep expertise in both large language models (LLMs) and agentic AI systems alongside a strong foundation in embedded systems development, enabling them to bridge the gap between cutting-edge AI innovation and the rigorous demands of storage firmware engineering.

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