Cortex Product Owner

Job Summary The Cortex Product Owner will define and prioritize an enterprise predictive AI platform spanning the model-development lifecycle. The role will drive secure self-service, automation, governance, migration, adoption, and measurable value across Google Cloud Platform-based AI and data services while coordinating technical and business stakeholders.

Key Responsibilities Define the product vision, roadmap, backlog, and service catalogue for the Cortex AI platform. Own self-service experiences across data preparation, experimentation, training, deployment, and monitoring. Prioritize capabilities across Vertex AI, BigQuery, GKE, AutoML, and workflow services. Establish MLOps and model-development lifecycle standards. Integrate security, data protection, model governance, compliance, and risk controls. Drive workload onboarding and migration from legacy or fragmented AI environments.

Define platform adoption, reliability, productivity, governance, and value metrics. Coordinate data, cloud, platform, security, risk, architecture, and business stakeholders. Manage product releases, feedback, dependency resolution, and continuous improvement. Required Qualifications 812 years of relevant professional experience. Strong experience in technical product management for cloud AI/ML platforms. Hands-on understanding of Google Cloud Platform AI and data services. Strong knowledge of Vertex AI, BigQuery, GKE, AutoML, and workflow orchestration.

Strong understanding of MLOps and the end-to-end model-development lifecycle. Experience with secure self-service platform design. Understanding of model governance, security, and risk controls. Experience managing roadmaps, backlogs, releases, migrations, and platform adoption. Strong senior stakeholder leadership and executive communication skills. Must be located in Charlotte, NC or the California Bay Area.

Preferred Qualifications Degree in engineering, computer science, data science, or a related field. Google Cloud Platform Professional Machine Learning Engineer, Cloud Architect, or equivalent certification. Experience managing an enterprise predictive AI or data-science platform.

Education: Bachelors Degree Certification: Google Cloud Platform Professional Machine Learning Engineer , Cloud Architect