At Cadence we hire and develop leaders and innovators who want to make an impact on the world of technology.
Agentic AI Engineer
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:Bachelors or Masters 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
Were doing work that matters. Help us solve what others cant.
Required Experience:
Unclear Seniority
At Cadence we hire and develop leaders and innovators who want to make an impact on the world of technology.Agentic AI EngineerAbout the RoleKey ResponsibilitiesBuild and deploy production-ready agentic AI applications using LangGraph and A2ADevelop and integrate AI assistant systems for real-world ...
At Cadence we hire and develop leaders and innovators who want to make an impact on the world of technology.
Agentic AI Engineer
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:Bachelors or Masters 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
Were doing work that matters. Help us solve what others cant.
Required Experience:
Unclear Seniority
View more
View less