Principal AI Workflow Engineer
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Job Description
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.
Key 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.
Requirements
Department: Datacenter Engineering
Function: Other
Experience Level: Not Applicable