Staff AI Solution Architect

About the role

At Cognichip, we're not just building AI; we're enabling our customers to harness the power of AI to transform their silicon design workflows. As an AI Application Engineer, you'll be the crucial link between our groundbreaking Artificial Chip Intelligence (ACI) solutions and the design teams who will use them. You'll translate complex technical concepts into practical solutions, helping teams successfully adopt our solutions and unleash their creativity.

Responsibilities

• Apply AI to real-world problems by serving as the primary technical point of contact for customers, providing expert guidance and support to help them integrate Cognichip ACI® solutions into their design flows.
• Bridge the gap by collaborating closely with customer design teams, providing hands-on support and troubleshooting to ensure a seamless experience. Act as the voice of the customer, relaying critical feedback and insights to our internal AI science and software teams.
• Drive adoption and success by developing and delivering technical presentations, demonstrations, and training sessions that showcase the value and capabilities of our solutions.
• Diagnose and solve customer-specific issues by analyzing design flows, log files, and user interactions to provide solutions and help improve our products and services.
• Educate and inform by creating clear, concise technical documentation, application notes, and guides to empower our customers and accelerate their learning curve.

Requirements

• Master's degree in Computer Science, Electrical Engineering, or a closely related field.
• 7 - 10 years of experience in RTL design, verification, or a combination of both, with a passion for customer-facing roles.
• Proficiency in Verilog/SystemVerilog and scripting languages like Python.
• Excellent written and verbal communication skills, with a strong ability to translate complex technical information into clear, actionable guidance.
• A consultative, problem-solving mindset and a passion for helping others succeed.
• Demonstrated knowledge of the chip design process, from RTL to physical design.

Skills

• Experience with machine learning or deep learning concepts is a strong advantage.