Sr. Principal Engineer, AI Systems and Solutions

Intel Corporation•Santa Clara, CA

10d•$255,850 - $413,520•Onsite

About The Position

Lead the definition and execution of system-level validation strategies across performance, power, and thermal domains while driving the transformation of validation methodologies through Generative AI. This role will establish scalable frameworks that automate validation planning, test creation, coverage analysis, and execution, improving product quality, accelerating development cycles, and increasing engineering efficiency.

Requirements

Strong expertise in system-level validation, including performance, power, and thermal characterization.
Proven experience building and deploying validation automation frameworks.
Hands-on experience with Python & automation tools.
Experience applying GenAI and Large Language Models (LLMs) to engineering workflows.
Demonstrated ability to lead cross-functional technical initiatives involving architecture, design, software, and validation teams.
Strong analytical, problem-solving, and leadership skills.
Track record of driving organizational transformation and adoption of new engineering methodologies.
Bachelor’s degree in electrical engineering, Computer Engineering, Computer Science, or a related field.
15+ years of experience in silicon, platform, or system validation.

Nice To Haves

Master’s or PhD in Electrical Engineering, Computer Engineering, Computer Science, AI/ML, or a related field.
Knowledge of AI-assisted test generation, coverage analysis, and validation methodologies.
Background in data analytics, machine learning, or intelligent workflow automation.

Responsibilities

Define and lead comprehensive system-level validation strategies, ensuring alignment between architecture, design specifications, and validation coverage.
Drive the adoption of GenAI and AgenticAI technologies to automate test plan generation, test development, coverage modeling, and gap analysis.
Partner with architecture, design, software, and product engineering teams to embed validation and automation requirements early in the development lifecycle.
Develop scalable AI-powered validation solutions that generate high-quality test content, coverage metrics, and validation workflows.
Establish best practices for AI-assisted validation and continuous process improvement.
Improve product quality, validation effectiveness, and defect detection while reducing manual effort through automation.
Utilize data-driven insights to measure, benchmark, and optimize validation efficiency and coverage.
Provide technical leadership and mentorship to engineers adopting advanced validation methodologies and GenAI-enabled workflows.