Overview
Keysight is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries.
Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.
As we expand our AI capabilities, we are integrating modern Large Language Models (LLMs) and Agentic AI systems into Electronic Design Automation (EDA) workflows. We are looking for engineers who can help build AI-powered tools, automation, and intelligent services for our next-generation platforms.
Responsibilities
- Develop and integrate LLM-based components into existing EDA tools and internal systems.
- Build and maintain MCP servers, AI services, and automation agents that enhance productivity and design workflows.
- Create prompts, conversational flows, and agent logic for AI-assisted engineering tools.
- Work with R&D teams to embed AI capabilities into real-world EDA use cases.
- Document workflows, integration steps, and best practices for AI-enabled components.
Qualifications
Programming
- Strong proficiency in Python.
- Experience with LLM frameworks, such as OpenAI, Anthropic, HuggingFace, or LangChain.
AI / LLM Skills
- Understanding of LLMs, prompt engineering, retrieval-augmented generation (RAG), agentic workflows, and tool-based AI.
- Ability to design small agent behaviors and integrate them with external APIs or internal tools.
Systems Integration
- Experience building microservices, MCP servers, REST APIs, or backend components.
- Familiarity with containerization (Docker), deployment basics, and service orchestration.
Data & EDA
- Basic understanding of data formats, preprocessing, and EDA workflows (training ML models is not the focus).
Additional Skills
- Strong analytical, communication, and problem-solving abilities.
- Ability to work independently and collaborate with R&D teams.
- Good documentation habits and willingness to learn new AI technologies quickly.
