Agentic AI Hardware Engineer

Overview

Agentic AI Hardware Engineer at Cadence

• Build and deploy production-ready agentic AI applications using Lang Graph and A2A
• Develop and integrate AI assistant systems for real-world design automation workflows
• Implement and maintain MCP servers for seamless tool integration in production environments
• Create practical AI solutions that directly enhance semiconductor design productivity

Education: Bachelor s or Master s degree in Electrical Engineering, Computer Science, or related field

• Lang Graph for multi-agent workflow orchestration
• Agent-to-Agent (A2A) communication frameworks
• Lang Chain, Llama Index, or similar LLM orchestration tools
• PyTorch, Tensor Flow, Hugging Face Transformers

• Strong OOP principles and design patterns in Python
• Experience with Python packaging, testing frameworks (pytest, unittest)
• Proficiency in async programming and concurrent systems
• RESTful API development and microservices architecture

• Experience building MCP servers for AI tool integration
• Understanding of protocol specifications and implementation patterns
• Knowledge of context management and state handling
• Deploy robust Python-based AI applications with focus on scalability and performance
• Translate business requirements into working AI applications and user interfaces
• Collaborate with design teams to implement AI solutions that solve immediate business challenges
• Support and maintain deployed AI applications, ensuring reliability and user satisfaction

We’re doing work that matters. Help us solve what others can’t.

• Entry level

• Full-time

• Engineering and Information Technology

• Software Development