Agentic AI Engineer

This role involves building and deploying production-ready agentic AI applications using LangGraph and A2A, developing and integrating AI assistant systems for real-world design automation workflows, and implementing MCP servers for seamless tool integration in production environments. The engineer will create practical AI solutions to enhance semiconductor design productivity, deploy robust Python-based AI applications, translate business requirements into AI solutions, and collaborate with design teams.

Must Have

• Build and deploy production-ready agentic AI applications using LangGraph 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
• Bachelor's or Master's degree in Electrical Engineering, Computer Science, or related field
• Proficiency in LangGraph for multi-agent workflow orchestration
• Proficiency in Agent-to-Agent (A2A) communication frameworks
• Proficiency in LangChain, LlamaIndex, or similar LLM orchestration tools
• Proficiency in PyTorch, TensorFlow, 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
• Experience with 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

About the Role

Key Responsibilities

• Build and deploy production-ready agentic AI applications using LangGraph 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

Required Qualifications

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

Core Frameworks:

• LangGraph for multi-agent workflow orchestration
• Agent-to-Agent (A2A) communication frameworks
• LangChain, LlamaIndex, or similar LLM orchestration tools
• PyTorch, TensorFlow, Hugging Face Transformers

Software Engineering:

• 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

MCP Development:

• 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