Senior R&D AI Software Development Engineer
Senior engineer on Keysight's R&D team building agentic AI for Electronic Design Automation (EDA) tools: MCP-based agent infrastructure, LLM-driven orchestration over simulation engines and product APIs, neural-network/surrogate modeling, and production Python backend services for high-speed digital design workflows.
- Compensation
- Not disclosed
- Location
- Singapore
- Work setup
- Onsite
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Must have
- Master's degree or PhD in Computer Science, Software Engineering, or a related field
- Strong software engineering skills in Python, with production-grade services, libraries, automation tools, or developer-facing APIs
- Hands-on experience with AI-agent or copilot-style solutions using LLMs, tool/function calling, planner-executor patterns, RAG, and agent orchestration frameworks
- Practical knowledge of Model Context Protocol (MCP): server/client concepts, tools, resources, prompts, schema design, secure tool invocation, deployment patterns
- Experience with AI/ML and neural-network concepts: deep learning, surrogate models, embeddings, vector databases, structured outputs, prompt engineering, context management
- Strong grasp of modern software-development practices: Agile, Git workflows, code review, CI/CD, automated testing, package management, security reviews, documentation
- Strong collaboration skills across multi-site, multi-cultural teams (R&D, product management, application engineering, customers)
- Clear written and spoken English communication for technical and management audiences
- Ability to guide development teams, mentor junior engineers, and drive pragmatic AI adoption
Nice to have
- Experience with EDA, CAD, simulation, high-speed digital design, signal/power integrity, RF/microwave, photonics, or scientific/engineering software
- Experience with product APIs, desktop application automation, Python scripting inside engineering tools, or AI-agent integration with domain software
- Familiarity with neural-network surrogate modeling for simulation acceleration, design-space exploration, and optimization
- Familiarity with LLM/agent frameworks, vector databases, knowledge graphs, semantic search, workflow orchestration platforms, or cloud deployment
- Exposure to C++, C#, TypeScript, or JavaScript
Full description
Overview
is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~16,800 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more
Our 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.
ResponsibilitiesAbout the Team
You will join a high-performing Keysight R&D team developing next-generation Electronic Design Automation (EDA) workflow solutions for High-Speed Digital (HSD), signal integrity, power integrity, and adjacent simulation-driven engineering domains. The team combines product APIs, simulation knowledge, AI/ML methods, neural-network modeling, and agentic workflow automation to help engineers interact more efficiently with complex design tools.
About the Job
As a Senior AI Software Development Engineer, you will develop agentic AI capabilities that connect large language models, EDA applications, simulation engines, product APIs, knowledge sources, and user workflows. Your work will enable supervised, goal-driven automation where AI agents can plan, invoke tools, reason over results, and assist with repeatable design-analysis tasks.
- Build and maintain MCP-enabled agent infrastructure, including servers, clients, skills, tool schemas, orchestration services, guardrails, and evaluation frameworks.
- Translate EDA workflow use cases into reliable AI-agent capabilities, such as simulation setup assistance, design diagnostics, optimization workflows, compliance-test setup, report generation, and guided automation.
- Apply neural-network techniques where appropriate, including surrogate modeling, embeddings, vector search, model evaluation, physics-aware or data-driven models, and AI-based acceleration of expensive simulation workflows.
- Develop production-quality backend services in Python and/or other modern languages with strong attention to reliability, observability, testing, maintainability, and secure deployment.
QualificationsTechnical Qualifications
- Master’s degree or PhD in Computer Science, Software Engineering, or a related field.
- Strong software engineering skills in Python, with experience building production-grade services, libraries, automation tools, or developer-facing APIs.
- Hands-on experience with AI-agent or copilot-style solutions using LLMs, tool calling/function calling, planner-executor patterns, retrieval-augmented generation, and agent orchestration frameworks.