Senior R&D AI Software Engineer

OverviewKeysight 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 about what we do.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.ResponsibilitiesWe are seeking an experienced Software Development Engineer to design and build end-to-end full-stack applications, encompassing intuitive frontend user interfaces and scalable backend services. This role involves developing responsive, user-friendly UI components using modern frameworks such as React or Vue, alongside building robust backend APIs and services (REST/GraphQL) to support application logic and data processing.You will integrate AI/ML capabilities, including large language model (LLM) APIs and other inference services, into production-ready systems, while architecting efficient data pipelines for ingestion, transformation, and storage to enable AI-driven features. The role requires optimizing performance, scalability, and reliability across the full stack, and working closely with R&D, product, and design teams to translate concepts into functional, user-facing solutions. You will operate in a fast-paced R&D environment, rapidly prototyping and iterating while maintaining high engineering standards, and contributing to architectural decisions and team mentorship.Key ResponsibilitiesDesign and develop end-to-end full-stack applications, including frontend interfaces and backend servicesBuild responsive, high-performance UIs using modern frameworks (e.g., React, Vue)Develop and maintain scalable backend systems and APIs (REST/GraphQL)Integrate and operationalize AI/ML capabilities (e.g., LLM APIs, inference services) into production systemsArchitect and implement data pipelines for AI-driven applicationsEnsure performance, scalability, and reliability across frontend and backend systemsCollaborate with cross-functional teams to deliver user-facing featuresRapidly prototype and iterate on new ideas in an R&D environmentImplement state management, caching, and asynchronous workflows for real-time interactionsDesign and manage cloud-based infrastructure (AWS)Apply best practices in code quality, testing, CI/CD, and system monitoringMonitor, debug, and optimize production systems (logging, observability, performance tuning)Ensure security and data privacy in system designMentor junior engineers and contribute to technical leadershipQualificationsMust-Have QualificationsMaster’s degree in Computer Science, Software Engineering, or a related field, with 5+ years of experience in full-stack software developmentStrong frontend expertise (React, Vue, or similar) and solid backend development skills (Python, Node.js, Java, or equivalent)Proven experience designing and building scalable APIs and systems, with strong fundamentals in system architecture and software designHands-on experience integrating AI/ML services (e.g., LLM or inference APIs) into production applicationsExperience with cloud platforms (AWS) and modern development practices (version control, testing, CI/CD)Demonstrated experience building scalable summarization/information extraction pipelines and production-grade anomaly detection or predictive models on numerical/time-series dataFamiliarity with Agile/Scrum methodologies and rigorous validation of ML/GenAI systems (evaluation metrics, bias/risk assessment)Strong problem-solving skills, ability to work independently, and effective cross-functional communicationFluency in English, including technical communicationStrongly PreferredExperience building AI-powered applications involving LLMs, generative AI, or real-time inference systemsFamiliarity with ML workflows, model evaluation, and performance optimizationExperience developing data-rich, interactive UIs (dashboards, visualizations, graphics-heavy applications)Hands-on experience with cloud-native architectures and containerization (Docker, Kubernetes)Experience with asynchronous processing, streaming systems, or real-time data pipelinesBackground in R&D or fast-paced product environments with rapid prototyping cyclesExposure to MLOps practices, monitoring, and observability toolsExperience mentoring engineers or contributing to technical leadershipExperience with Model Context Protocol (MCP) for standardized, secure integration between LLM systems and external data sources, tools, or enterprise services.