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. 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.
Keysight's products address a variety of Test and Measurement requirements for 6G, Commercial Communications, EDA, Automotive, Semi-Conductor Test, Energy and Aero/Defense markets. Within Keysight - the Secure Software Factory (SSF) and R&D productivity initiative aim to integrate Artificial Intelligence tools to accelerate software development lifecycle (SDLC) along with adopting the enterprise DevSecOps platform.
Responsibilities
We have an opportunity for AI R&D Engineer, to
- Design, build, and integrate AIpowered applications and services that accelerate software delivery and developer experience.
- Turn problem statements into productiongrade solutions (LLMassisted features, RAG/agent workflows, AIaugmented test automation) - ensure secure, compliant use of AI across the SDLC
- Enable integration of commercial AI tooling and SaaS solutions for inducting Agentic AI into Keysight's Software Engineering and R&D functions
Specific Responsibilities
AI Application Development
- Partnering with IT to drive delivery of new features to internal functions to accelerate SDLC phases.
- Combine classical ML, retrieval/agent patterns and leverage LLM capabilities to deliver robust APIs, microservices, and frontends.
- Create goldenpath reference components for common scenarios (code assistance, documentation summarization, knowledge search, test plan generation).
- Demonstrate and productionize agentic workflows for security scanning, remediation and pipeline automation
Platform & Integration
- Integrate solutions for central tools (Atlassian's Jira, Bitbucket, confluence, Docker, Kubernetes, Jenkins, VMware, Cloud Bees CI/CD etal.)
- Collaborate with Secure Software Factory (SSF) and Product Security Applications teams to fold AI features into standard SDLC workflows.
Engineering Intelligence & Telemetry (SEI)
- Help setup telemetry end points and Build dashboards/reports that gather adoption, utilization and capture real time value benefits of AI models and toolings.
Quality, Test & Reliability
- Design test strategies for AI features (unit, integration, adversarial, modelintheloop); apply Human and AIassisted testing and demonstrate selfhealing approaches where suitable.
Security, Privacy & Compliance
- Translate corporate AI governance into developer friendly approaches: data handling, prompt safety, model access tiers, applying vendor usage rules.
Collaboration & Enablement
- Partner with guilds/forums (NPC, enablement sessions) to share best practices, reusable assets, and developer training content.
- Participate in coordination with IT for releases to ensure new feature releases are tested and enabled for Software Engineers at large.
Qualifications
Education
- Bachelor's or master's in computer science, Electrical/Electronic Engineering, or related field; advanced ML/AI coursework or certifications preferred.
Experience
- 24 years in Computer / Software engineering (backend/frontend) with handson AI/ML application development or integration; internships/projects count toward demonstrable capability
- Programming: Proficiency in Python and C#/JavaScript/TypeScript; strong API design (REST/GraphQL), microservices.
- AI/ML: Practical experience with LLM tooling (prompting, evaluation, safety), RAG (embeddings/vector stores), and at least one framework (PyTorch, TensorFlow).
- Cloud & DevOps: Experience on Azure (preferred) or AWS CI/CD, containers (Docker/K8s), observability (logs/metrics/traces).
- Toolchain: GitHub, Jira/Confluence, Microsoft 365; familiarity with GitHub Copilot and M365 Copilot for developer productivity.
- Security & Compliance: Ability to implement secure leastprivilege, data minimization, and secure prompt/data flows.
- Soft skills: Clear communication, collaboration across global teams, and a builder's mindset with ownership of outcomes.
Preferred
- Exposure to NIST SSDF practices (https://csrc.nist.gov/projects/ssdf#ssdf-practices) and integrating AI features into standard Keysight SDLC
- Frontend skills (Angular/React) to deliver endtoend AIaugmented workflows.
- Experience contributing to enablement of guilds or creating internal playbooks/tutorials.
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***
