Senior Design Verification Engineer

Job Title Senior Design Verification Engineer About Cognichip - At Cognichip, we are building AI-native tools that transform how semiconductor engineers create, verify, and optimize chips. - Our platform combines large proprietary models, agentic workflows, domain-specific engineering intelligence, and high-performance simulation infrastructure to accelerate one of the world's most complex engineering disciplines. About the Role - We are seeking a Senior Design Verification Engineer who can combine strong verification expertise with applied AI/ML collaboration to help build production-grade tools for chip verification. - In this role, you will help turn advanced research ideas into practical workflows used by engineers verifying real silicon. - This work matters because verification is one of the biggest bottlenecks in modern chip design, and AI-native systems can meaningfully change the speed, quality, and scale of verification work. Key Responsibilities - Bridge Hardware and Software: Translate verification domain expertise into clear requirements that inform tool development and model behavior. - Support Data Pipelines: Contribute to workflows that generate synthetic or augmented verification code and testbenches, creating the datasets needed to train and evaluate AI models. - Workflow Optimization: Help refine automated workflows for verification-related tasks such as test planning, coverage analysis, and bug triage. - Infrastructure Support: Build and maintain simulation and testing infrastructure to validate AI-generated verification artifacts. - Collaboration: Work closely with AI researchers, software engineers, and other hardware engineers to ensure verification requirements are accurately reflected in tools and models. Required Qualifications - Experience: 5–8+ years of experience in design verification or hardware-focused software development. - Verification Domain: Strong understanding of verification methodologies and testbench development for digital designs. - EDA Tools: Practical experience with industry-standard simulation and verification tools. - Software Proficiency: Solid programming skills in Python, C++, or similar languages. - AI/ML Exposure: Interest in or exposure to LLMs, prompt engineering, or machine learning frameworks applied to technical domains (prior hands-on ML experience is a plus, not required). - Education: BS, MS, or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field. Preferred Qualifications - Experience contributing to or building automated/agentic workflows for engineering tasks. - Background in computer architecture, particularly for AI accelerators or high-performance computing. - Contributions to open-source hardware or AI projects. What It's Like Here - We're a fast-moving AI startup with a collaborative, high-trust culture. - We value technical excellence, ownership, and the freedom to experiment. - Our best work happens when our builders and innovators work closely together to turn ambitious ideas into category-defining products. - We operate on a hybrid schedule with four days in office, one day remote. - If you're excited to build tools that empower semiconductor engineers and reshape how chips are verified, you'll feel right at home.