Senior Principal AI Architect

Keysight Technologies, Inc.•Barcelona, Colorado

About The Position

Software & AI Labs is seeking a Senior Principal AI Architect to define enterprise AI architecture and accelerate adoption across Keysight. This role will shape reusable platforms, customer-facing solutions, and scalable adoption patterns that connect AI Labs investments to Keysight’s growth priorities and customer opportunities. The Senior Principal AI Architect will set technical standards, design principles, and architecture direction for AI-enabled platforms and solutions. This senior individual contributor role requires leadership through influence, technical credibility, executive communication, and cross-functional collaboration. The successful candidate will translate AI Labs’ strategy into architectural priorities, technology roadmaps, reusable capabilities, and execution guidance that accelerate adoption, reduce duplication, and create measurable enterprise value.

Requirements

Advanced degree in Computer Science, Electrical Engineering, or a related field, or equivalent professional experience.
Typically requires 10+ years of experience in senior technical architecture roles with increasing scope and measurable business impact.
Expertise in one or more areas such as applied AI, machine learning systems, data platforms, software architecture, or AI-enabled product development.
Strong systems thinking, with the ability to turn recurring use cases into reusable capabilities, standards, and platforms.
Experience in senior technical leadership roles such as Principal Architect, Chief Architect, Distinguished Engineer, Technical Fellow, or equivalent.
Experience with measurement instrumentation and test workflows in RF and digital domains, including how software, data, and automation capabilities interface with complex electronic test systems.
Ability to define and execute technical architecture across multiple engineering teams, product domains, platforms, or business units.
Experience designing scalable, reusable, production-grade platforms or frameworks that support multiple use cases, teams, or customer-facing solutions.
Strong understanding of modern AI system design, including data pipelines, MLOps, evaluation methods, deployment patterns, governance, and lifecycle management.
Demonstrated ability to translate business strategy into technical strategy, architectural priorities, execution plans, and measurable outcomes.
Experience integrating AI capabilities into commercial software products, engineering workflows, test and measurement systems, or other technically complex customer-facing solutions.
Ability to operate as a senior individual contributor with broad influence across engineering, product, research, business, and executive stakeholders.
Excellent communication skills, including the ability to explain complex technical concepts to executive audiences, business stakeholders, and engineering teams.
Ability to lead through influence, mentor senior technical talent, resolve architectural ambiguity, and drive alignment across teams without direct management authority.

Nice To Haves

Experience building enterprise AI platforms, agentic systems, model development environments, data science platforms, or AI-enabled product ecosystems.
Experience with agentic orchestration, LLM-based systems, retrieval-augmented generation, foundation models, model evaluation, AI governance, or domain-specific automation.
Experience deploying models on hardware platforms, including real-time environments such as FPGAs, GPUs, or NPUs.
Familiarity with cloud infrastructure, CI/CD, compute governance, data governance, security review, software supply chain practices, and production operations.
Strong background in architecture review boards, technical governance forums, design review processes, or enterprise technology standards.
Experience working across centralized innovation teams and distributed business unit teams where success depends on shared ownership, influence, and adoption.
Ability to balance innovation speed with architectural discipline, production reliability, security, maintainability, and long-term platform leverage.

Responsibilities

Define and communicate an enterprise AI architecture vision that aligns AI Labs investments with customer needs, business unit priorities, and emerging technology trends.
Establish reusable architecture patterns that improve interoperability, scalability, maintainability, production readiness, and business unit adoption.
Partner with AI Labs leadership and senior Keysight stakeholders to shape long-term technology strategy, roadmaps, and architectural priorities.
Drive architectural consistency across AI Platform, Models & Data Science, Agentic Framework initiatives, and product teams through standards, reference architectures, and design patterns.
Identify common capabilities across programs and business unit engagements to reduce duplication and increase reuse of platforms, datasets, models, tools, and engineering patterns.
Review major AI initiatives to ensure solutions are scalable, maintainable, secure, supportable, and aligned to measurable business value.
Build alignment across business units and partner organizations by clarifying architectural tradeoffs and helping teams converge on scalable implementation paths.
Mentor architects, senior engineers, product leaders, and technical contributors through design reviews, technical guidance, architecture forums, and thought leadership.
Guide technology selection, architectural decisions, and intellectual property development to ensure that AI Labs investments create durable technical advantage and long-term strategic value.