Principal AI Workflow Engineer

Join a multibillion-dollar global company that brings together amazing technology, people, and operational scale to become a powerhouse in the memory industry. Headquartered in Rancho Cordova, California, Solidigm combines elements of an established, successful technology company with the spirit, agility, and entrepreneurial mindset of a start-up. In addition to the U.S. headquarters and other facilities in the U.S., the company has international presence in Asia, Europe, and the Americas. Solidigm will continue to lead the world in innovating new Memory technologies with aspirations to be the #1 NAND memory company in the world. At Solidigm, we view problems as opportunities to define innovative solutions that hold the power to change the world and unleash the potential technological needs that the future holds. At Solidigm, we are One Team that fosters a diverse, equitable, and inclusive culture that embraces individual uniqueness and empowers us to bring our best selves to deliver excellence in support of Solidigm's vision and mission to be the go-to partner for optimized data storage solutions. You can be part of the takeoff of an innovative business that develops cutting-edge products, delivers strong business value for customers, provides an engaging workplace for its employees, and serves a greater impact on the world. This is a golden opportunity for the right applicant to join us and help design, build, and lead Solidigm. We want a diverse team of dedicated professionals who will not just be Solidigm team members but contribute to how we shape the future of the organization. We are seeking applicants who will grow and thrive in our culture; be customer inspired, trusting, innovative, team-oriented, inclusive, results driven, collaborative, passionate, and flexible.

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.

Candidates must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. Requirements listed below would be obtained through a combination of schoolwork/classes/research and/or relevant previous job and/or internship experiences.

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.

Preferred Qualifications

• 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.).

This position is also eligible to participate in Solidigm's restricted stock unit (RSU), restricted cash unit (RCU), and cash bonus programs. In addition, Solidigm offers a benefits package that includes medical, dental, vision, supplemental life and AD&D insurance; short- and long-term disability; healthcare and dependent care flexible spending accounts, and a company match on eligible 401(k) plan contributions.

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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