AI Solution Engineer - FPGA

Job Summary

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 with an FPGA focus, you’ll be the crucial link between our groundbreaking Artificial Chip Intelligence (ACI) solutions and the hardware design teams who will use them to target high-performance FPGA platforms. You’ll translate complex technical concepts into practical solutions, helping teams successfully adopt our solutions and unleash their creativity on programmable logic.

If you thrive on solving technical challenges and empowering others to build the future of accelerated computing, this is your stage.

Staff AI Solution Engineer – FPGA

• Apply AI to real-world problems. Serve as the primary technical point of contact for customers, providing expert guidance and support to help them integrate Cognichip ACI® solutions into their FPGA-based design flows and hardware acceleration pipelines.
• Bridge the gap. Collaborate closely with customer design teams, providing hands‑on support for RTL development, optimization, and hardware troubleshooting to ensure a seamless experience when going from innovative idea to reconfigurable chips. You’ll also act as the voice of the customer, relaying critical feedback to our AI science and software teams.
• Drive adoption and success. Develop and deliver technical presentations, hardware demonstrations, and training sessions that showcase the value and capabilities of ACI for the FPGA hardware and software ecosystems.
• Diagnose and solve. Dive deep into customer‑specific issues—analyzing design flows, log files, and user interactions—to diagnose problems, provide solutions, and help improve our products and services.
• Educate and inform. Create clear, concise technical documentation, application notes, and reference designs for FPGA implementation to empower our customers and accelerate their learning curve.

• Master’s degree in Electrical Engineering, or a closely related field.
• 7 to 10 years of experience in FPGA-based RTL design, verification, and optimization, with a passion for customer‑facing roles.
• Proficiency in Verilog/System Verilog, FPGA tool chains (AMD/Altera), 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 full FPGA design process, from RTL to synthesis and timing closure.
• Experience with machine learning or deep learning concepts is a strong advantage.