R&D Engineer 4, Software
Confirmed on the employer's own hiring board on Oct 11, 2026. First seen by Alion on Apr 21, 2026.
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.
Role Overview
We are looking for a Technical MarketingEngineerwho can bridge the gap between our AI engineering teams and the broader R&D organizationby grooming usecaseand enabling them end-to-end. You will be the internal champion of Keysight’s AI productivity tools-crafting compelling narratives, delivering polished live demos to R&D teams and senior executives, creating technical content that accelerates adoption and workflow integration, and building internal excitement that translates into measurable value creation. This is a purely internal, R&D-focused role that requires equalpartstechnical depth and marketing creativity: you need to understand how an AItoolworks under the hood AND know how to make an audience of engineers lean forwardand adopt thetools.
Responsibilities
Key Responsibilities
Demos & Technical Storytelling
- Design and deliver compelling, polished live demonstrations of AI productivity tools to R&D teams, engineering leadership, and senior executives-at internal summits, executive briefings, town halls, and cross-functional reviews.
- Build andmaintaina library of demo environments, scripts, and narratives tailored to different internal audience personas (R&D engineers, engineeringleads, VPs).
- Create high-impact demo videos, tutorials, and interactive walkthroughs that drive internal adoption and excitement across engineering groups.
- Translate complex AI/ML capabilities (LLM-powered assistants, ML-driven simulation, predictive analytics) into clear, benefit-driven stories that resonate with technical and executive audiences.
Internal Communications & Technical Content
- Own the internal positioning, messaging, and value proposition for Keysight’s AI productivity tools-ensuring consistency across internal communications, executive presentations, and R&D enablement materials.
- Develop and execute internal launch strategies for new AI features in partnership with product management, engineering leadership, and R&D teams.
- Create technical white papers, internal newsletters, knowledge base articles, solution briefs, andadoption ofsuccess stories that build momentum for AI tool usage across the organization.
- Develop executive-ready materials (briefing decks, ROI narratives, adoption dashboards) that articulate the impact and value of AI productivity initiatives to senior leadership.
R&D Adoption & Workflow Integration
- Embedwithin R&D engineering teams to deeply understand their workflows, pain points, and adoption barriers-and equip them with training, toolkits, and best practices for AI productivity features.
- Collaborate with product management and engineering leadership to influence the product roadmap based on internal user feedback,adoption and impactmetrics, andseedengineering conversationson use of AI for success.
- Serve as the connective tissue between the AI Productivity group and the broader R&D organization-running internal roadshows, lunch-and-learns, and hands-on workshops to accelerate workflow integration.
- Define and trackadoption ofKPIs (active users, workflow integration depth, time savings, value created) and report progress to leadership with data-driven narratives.
- Gather and synthesize feedback from R&D teams and executives to inform tool priorities, messaging, and the internal adoption strategy.
Careers Privacy Statement ***Keysight is an Equal Opportunity Employer.***
Qualifications
Preferred Qualifications
- Master's degree in engineering, MBA, or graduate work in AI/ML or data science.
- Background in R&D environments within semiconductor, test & measurement, or engineering software industries.
- Experience championing AI-powered developer tools, copilots, or intelligent assistants internally (e.g., AI coding assistants, intelligent automation tools).
- Hands-on familiarity with AI/ML frameworks (TensorFlow,PyTorch) or scripting languages (Python) for building demo environments.
- Experience driving internal technology adoption programs or change management initiatives in engineering organizations.
- Track recordof building executive-level presentations and narratives that influence strategic decisions.
Skills & Competencies
Compelling Demos
Captivates audiences with polished, narrative-driven live product demonstrations
Technical Fluency
Discusses AI/ML architecture, LLMs, and engineering workflows with credibility
Storytelling & Messaging
Transforms complex technology into clear, benefit-driven narratives
Cross-Functional Influence
Drives alignment across R&D engineering, product, and executive leadership
Adoption Strategy
Designs and executes internal programs that turn awareness into active usage
Content Creation
Produces high-quality technical content-white papers, internal blogs, videos, and enablement materials
Key Responsibilities
Demos & Technical Storytelling
- Design and deliver compelling, polished live demonstrations of AI productivity tools to R&D teams, engineering leadership, and senior executives-at internal summits, executive briefings, town halls, and cross-functional reviews.
- Build andmaintaina library of demo environments, scripts, and narratives tailored to different internal audience personas (R&D engineers, engineeringleads, VPs).
- Create high-impact demo videos, tutorials, and interactive walkthroughs that drive internal adoption and excitement across engineering groups.
- Translate complex AI/ML capabilities (LLM-powered assistants, ML-driven simulation, predictive analytics) into clear, benefit-driven stories that resonate with technical and executive audiences.
Internal Communications & Technical Content
- Own the internal positioning, messaging, and value proposition for Keysight’s AI productivity tools-ensuring consistency across internal communications, executive presentations, and R&D enablement materials.
- Develop and execute internal launch strategies for new AI features in partnership with product management, engineering leadership, and R&D teams.
- Create technical white papers, internal newsletters, knowledge base articles, solution briefs, andadoption ofsuccess stories that build momentum for AI tool usage across the organization.
- Develop executive-ready materials (briefing decks, ROI narratives, adoption dashboards) that articulate the impact and value of AI productivity initiatives to senior leadership.
R&D Adoption & Workflow Integration
- Embedwithin R&D engineering teams to deeply understand their workflows, pain points, and adoption barriers-and equip them with training, toolkits, and best practices for AI productivity features.
- Collaborate with product management and engineering leadership to influence the product roadmap based on internal user feedback,adoption and impactmetrics, andseedengineering conversationson use of AI for success.
- Serve as the connective tissue between the AI Productivity group and the broader R&D organization-running internal roadshows, lunch-and-learns, and hands-on workshops to accelerate workflow integration.
- Define and trackadoption ofKPIs (active users, workflow integration depth, time savings, value created) and report progress to leadership with data-driven narratives.
- Gather and synthesize feedback from R&D teams and executives to inform tool priorities, messaging, and the internal adoption strategy.
Careers Privacy Statement ***Keysight is an Equal Opportunity Employer.***
Preferred Qualifications
- Master's degree in engineering, MBA, or graduate work in AI/ML or data science.
- Background in R&D environments within semiconductor, test & measurement, or engineering software industries.
- Experience championing AI-powered developer tools, copilots, or intelligent assistants internally (e.g., AI coding assistants, intelligent automation tools).
- Hands-on familiarity with AI/ML frameworks (TensorFlow,PyTorch) or scripting languages (Python) for building demo environments.
- Experience driving internal technology adoption programs or change management initiatives in engineering organizations.
- Track recordof building executive-level presentations and narratives that influence strategic decisions.
Skills & Competencies
Compelling Demos
Captivates audiences with polished, narrative-driven live product demonstrations
Technical Fluency
Discusses AI/ML architecture, LLMs, and engineering workflows with credibility
Storytelling & Messaging
Transforms complex technology into clear, benefit-driven narratives
Cross-Functional Influence
Drives alignment across R&D engineering, product, and executive leadership
Adoption Strategy
Designs and executes internal programs that turn awareness into active usage
Content Creation
Produces high-quality technical content-white papers, internal blogs, videos, and enablement materials