Senior AI Automation Engineer

Cornelis Networks is building the future of AI and HPC networking with an AI-first approach to silicon and software development. They are seeking a Senior AI Automation Engineer to develop high-performance ASIC design workflows using AI, focusing on optimizing design and verification flows, and driving efficiencies with AI and automation across tools and EDA workflows.

Responsibilities:

• Lead the optimization of ASIC design and verification flows and infrastructure, including compute clusters, storage, batch queuing systems using AI methodologies
• Drive efficiencies with AI and automation across all tools and EDA workflows. Perform tool license management and optimization on batch compute environment
• Manage ASIC tool installation, environment setup, and licensing support for ASIC design and AI applications
• Collaborate with design and verification teams, IT, and engineering leadership to implement scalable and efficient workflows
• Drive process improvements, patch management, and operational efficiency across multiple sites
• Implement and maintain metrics reporting for resource utilization, engineering productivity, and system performance

Requirements:

• B.S. or M.S. degree in Computer Engineering, Computer Science, Electrical Engineering, or related field
• 10+ years of experience supporting ASIC EDA environments in multi-site, global organizations. Strong exposure to AI
• Strong expertise in Linux administration, batch systems (LSF, Slurm), storage (NetApp, Isilon, Qumulo), and VDI environments
• Experience with EDA tools and ASIC workflows, including tool installation, licensing, and operational support
• Scripting and automation experience (Python, Tcl, Bash) to support HPC/EDA operations and productivity
• Proven ability to lead teams, collaborate across global sites, and manage projects with complex infrastructure dependencies
• Excellent communication skills to interface with design teams, IT, and vendors
• Large-scale data center EDA environment and AI projects
• Cloud HPC deployments and cost optimization strategies (Azure, CycleCloud, HPC burst management)
• Implementing metrics-driven operations for system performance and engineering productivity