C
Principal Agentic AI Engineer - Analog Design Automation
Actively Hiring
Full-time Posted 2 months ago
Responsibilities
- check_circle Design, develop, and deploy agentic AI workflows that automate analog semiconductor design and verification processes.
- check_circle Build AI agents leveraging existing Large Language Models (LLMs) to improve engineering productivity across analog development flows.
- check_circle Develop reusable AI Skills, MCP (Model Context Protocol) tools, and workflow orchestration components with an emphasis on efficient token utilization, context management, and scalability.
- check_circle Collaborate with analog design, layout, and physical verification teams to identify automation opportunities and deliver production-ready AI solutions.
- check_circle Develop robust software using Python and modern DevOps practices, including CI/CD pipelines, workflow automation, and version-controlled development.
- check_circle Integrate AI solutions with EDA environments using Tcl, Python, Rust and other scripting languages.
- check_circle Optimize AI workflows for performance, reliability, security, and cost efficiency.
- check_circle Lead architecture discussions and mentor engineers on AI-driven semiconductor automation technologies.
- check_circle Stay current with advances in Generative AI, LLMs, Agentic AI, and semiconductor design automation.
Basic qualifications
- Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related technical discipline.
- 8+ years of experience in analog semiconductor development workflow automation.
- 8+ years of experience in physical verification, including signoff verification methodologies.
- 8+ years of experience developing high-speed analog custom layouts.
- Proven experience designing and implementing agentic AI workflows using existing Large Language Models (LLMs).
- Experience developing AI Skills, MCP tools, and agent orchestration frameworks with efficient token utilization strategies.
- Strong programming skills in Python.
- Experience with DevOps methodologies, CI/CD pipelines, software engineering best practices, and version control systems.
- Strong scripting experience using Tcl.
- Thorough understanding of:
- Analog floorplanning
- Device matching and analog layout techniques
- EM/IR analysis and power planning
- Parasitic RC extraction and tradeoff analysis
- High-speed analog design methodologies
- Simulation methods
Preferred qualifications
- Experience integrating AI solutions with commercial EDA tools such as Cadence, Synopsys, or Siemens EDA.
- Experience with Retrieval-Augmented Generation (RAG), vector databases, and AI knowledge management systems.
- Familiarity with Model Context Protocol (MCP) architecture and AI tool development.
- Experience deploying AI applications on cloud or hybrid computing platforms.
- Knowledge of modern LLM frameworks such as LangGraph, LangChain, Semantic Kernel, CrewAI, or AutoGen.
- Experience building production-grade AI systems with observability, monitoring, evaluation, and governance.
- Agentic AI
- Large Language Models (LLMs)
- MCP (Model Context Protocol)
- Python
- Tcl
- Rust
- DevOps and CI/CD
- Workflow orchestration
- Analog Custom Layout workflow
- Analog Design workflow
Tags & Focus Areas
Remote Ai Ai Engineer Generative Ai