Product Manager (AI Platforms)

Keysight Technologies, Inc.•Loveland, CO

1d•Hybrid

About The Position

Keysight Technologies is hiring an Expert Product Manager to own the AI Platform within Software & AI Labs. The AI Platform is the internal foundation on which Keysight's AI solutions are built, enabling teams to move from data to deployable models with speed, consistency, and scale. This is an expert individual contributor role operating at the center of AI Labs. The successful candidate will drive cross-organizational adoption of the AI Platform as a shared service, partnering with platform engineering, model development, business units, and application teams to standardize how AI is built, validated, packaged, and deployed across Keysight. The role begins with internal enablement as the primary mandate; scaling the platform into customer-facing capability is a future-state objective, not a day-one deliverable.

Requirements

Bachelor's degree or above in Engineering, Computer Science, or related field
7+ years of product management experience, with demonstrated ownership of platform or infrastructure products
Proven ability to define and scale platforms and end-to-end products across multiple stakeholder groups
Experience driving cross-organizational alignment and adoption at scale
Familiarity with the Electronic Test & Measurement industry
Independent professional who operates effectively with broad direction

Nice To Haves

Experience with MLOps platforms, data infrastructure, or AI development frameworks
Familiarity with RF, hardware-integrated, or automation workflows
Experience scaling internal platforms into customer-facing products
Ability to translate technical systems into clear business value

Responsibilities

Define and own the vision, roadmap, and success metrics for the AI Platform
Establish the AI Platform as the standard framework for AI model lifecycle execution across Keysight
Sequence the platform's evolution from internal enablement tool toward eventual customer-facing capability
Drive adoption of the AI Platform across business units as a shared service model
Represent platform strategy to global stakeholders, including engineering leaders, business unit GMs, and solution owners
Translate solution-specific needs into scalable, reusable platform capabilities
Enforce a platform-first approach, reducing one-off implementations and fragmentation
Own definition and delivery of core platform capabilities across the AI lifecycle (data preparation, training, validation, packaging, deployment)
Define APIs and integration patterns across instruments, automation frameworks, and software systems
Partner with engineering to deliver high-quality, scalable capabilities on committed timelines
Define what constitutes a production-ready AI deliverable and establish clear handoff points from central AI teams to business units
Partner with product and solution teams to align customer use cases to platform capabilities
Ensure workflows are production-ready and reusable across solutions
Prepare the platform for future integration into commercial offerings
Define, track, and drive improvement in adoption and impact metrics, including: Number of AI solutions built on the platform, Reduction in model development-to-deployment cycle time, Percentage of AI work executed on-platform vs. off-platform, Internal user satisfaction and time-to-first-model for new teams