3 days ago
Singapore, SingaporeSenior
Responsibilities
- 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 AI-agent capabilities for simulation setup, design diagnostics, optimization, compliance-test setup, report generation, and guided automation.
- Apply neural-network techniques such as surrogate modeling, embeddings, vector search, model evaluation, and physics-aware or data-driven modeling to engineering workflows.
- Develop reliable, observable, testable, maintainable, and secure production backend services in Python and other modern languages.
- Collaborate with R&D, product management, application engineering, and customer-facing stakeholders.
- Guide development teams, mentor junior engineers, and drive pragmatic AI adoption in production engineering software.
Requirements
- Master’s degree or PhD in Computer Science, Software Engineering, or a related field.
- Strong Python software engineering skills and experience building production-grade services, libraries, automation tools, or developer-facing APIs.
- Hands-on experience with LLM agents or copilot-style solutions, tool or function calling, planner-executor patterns, retrieval-augmented generation, and agent orchestration frameworks.
- Practical knowledge of Model Context Protocol, including server and client concepts, tools, resources, prompts, schema design, secure tool invocation, and local or remote deployment.
- Knowledge of AI/ML and neural-network concepts including deep learning, surrogate models, embeddings, vector databases, structured outputs, prompt engineering, and context management.
- Understanding of software development practices including Git workflows, code review, automated testing, package management, security reviews, and documentation.
- Preferred experience with EDA, CAD, simulation, high-speed digital design, signal integrity, power integrity, RF/microwave design, photonics, or scientific and engineering software.
- Preferred experience with product APIs, desktop application automation, Python scripting inside engineering tools, or AI-agent integration with domain-specific software.
- Preferred familiarity with LLM application frameworks, agent frameworks, vector databases, knowledge graphs, semantic search, workflow orchestration platforms, or cloud deployment environments.
- Exposure to C++, C#, TypeScript, or JavaScript is beneficial.
- Strong collaboration, communication, mentoring, and technical explanation skills.
Tech Stack
Categories
About Keysight
Keysight Technologies builds electronic test and measurement instruments and software used for design, validation, and manufacturing by engineers in communications, semiconductor, aerospace and defense, automotive, and data center markets. Its portfolio includes oscilloscopes, signal and network analyzers, RF/microwave test systems, and EDA and network test software, sold with services and support. Founded in 2014 as a spin-off from Agilent Technologies, Keysight is a public company (NYSE: KEYS) headquartered in Santa Rosa, California.