Principal AI Workflow Engineer

Solidigm•Rancho Cordova, CA

12h•$196,240 - $314,000

About The Position

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.

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.

Nice To Haves

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.).

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.