Agentic AI Engineer
9 Minutes ago • All levels
Research Development
Job Description
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
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