Principal Lead Engineer

Stonegate Workforce Group is recruiting for an unnamed technology company developing a Physics AI platform for semiconductor engineering. The Senior / Principal Lead Delivery Engineer will lead customer-facing semiconductor engineering engagements from discovery through deployment, coordinating multidisciplinary teams and integrating simulation and AI solutions into customer workflows.

Responsibilities:

• Serve as a primary technical point of contact for external semiconductor customers, including semiconductor equipment manufacturers, chip designers, foundries, and advanced packaging organizations
• Lead technical discovery sessions to understand customer engineering challenges, requirements, and business objectives
• Build relationships with customer engineering teams, technical decision-makers, and executive stakeholders
• Translate complex semiconductor engineering challenges into actionable technical solutions
• Present technical recommendations, communicate project progress, and manage customer expectations
• Collaborate directly with customer engineering teams throughout solution development and implementation
• Own customer engagements from initial scoping through model development, deployment, and implementation
• Develop Statements of Work (SOWs), establish project milestones, and manage technical deliverables
• Lead cross-functional teams of applications engineers, AI/ML scientists, data engineers, and product engineers
• Manage project timelines, sprints, resources, risks, and stakeholder expectations
• Identify and resolve technical roadblocks to ensure projects remain on track
• Maintain accountability for successful delivery, customer satisfaction, and measurable engineering outcomes
• Balance technical project execution with product development priorities and customer requirements
• Apply semiconductor engineering and multiphysics simulation expertise to solve complex technical challenges
• Support applications involving electronic design automation (EDA), chip thermal analysis, electromagnetics, signal and power integrity, fluid dynamics, and structural mechanics
• Work with semiconductor capital equipment applications involving etch, deposition, lithography, and metrology
• Collaborate with AI/ML teams to develop and deploy physics-based machine learning solutions
• Remain technically hands-on with Python, scripting, simulation tools, models, and engineering workflows
• Support the integration of advanced simulation and AI technologies into customer engineering environments
• Translate customer feedback into recommendations for future product capabilities

Requirements:

• 5–10+ years of relevant experience in semiconductor engineering, simulation, R&D, advanced engineering, technical program management, or applied AI/ML
• Strong understanding of multiple semiconductor engineering disciplines, including EDA, thermal analysis, electromagnetics, signal and power integrity, or multiphysics simulation
• Demonstrated experience independently managing complex technical or engineering projects from initiation through delivery
• Proven experience working directly with external semiconductor customers, including leading technical discussions, managing expectations, and delivering engineering solutions
• Experience leading multidisciplinary engineering teams and coordinating technical resources without direct reporting authority
• Strong project management capabilities, including SOW development, milestone tracking, risk management, and execution
• Hands-on experience with Python, scripting, engineering simulation tools, and AI/ML workflows
• Working knowledge of machine learning applications in engineering, including surrogate modeling, neural operators, physics-informed machine learning, or digital twins
• Strong technical communication, presentation, and stakeholder management skills
• Ability to work independently in a remote, customer-facing environment
• Willingness to travel approximately 10–25% to customer sites
• Master's degree or PhD in Electrical Engineering, Mechanical Engineering, Materials Engineering, or a related technical discipline
• Experience with semiconductor capital equipment manufacturers such as Applied Materials, Lam Research, KLA, ASML, or Tokyo Electron
• Background working with chip designers or foundries such as NVIDIA, AMD, Intel, TSMC, Samsung, Qualcomm, or Broadcom
• Experience with fab equipment engineering, advanced packaging, chiplets, 2.5D/3D integration, or high-bandwidth memory (HBM)
• Experience deploying AI/ML or advanced engineering simulation solutions into production workflows
• Background in engineering software, semiconductor technical consulting, or customer-facing engineering delivery