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.