Enterprise AI Architect: Build Scalable, Reusable Patterns

GE Vernova; Greenville (SC); On-site; USD 113,200 - 188,800; Full time

Benefits offered by this job

Relocation assistance

Discretionary annual bonus

Comprehensive benefits

Tuition assistance

Job summary

GE Vernova is seeking a Senior AI Architect to define scalable AI architectures and enforce reusable patterns across Wind Engineering.

The role mentors Embedded AI Architects, drives AI standards, and partners with Digital/IT to establish MLOps and integration best practices for enterprise platforms. You will guide security, data governance, model risk, and quality management as AI capabilities expand across projects.

Qualifications

• Designing, building, and deploying AI solutions at enterprise scale.
• Defining technical standards, reference architectures, and design practices.
• Experience with AI/ML domains including supervision, time-series, and generative AI.
• Familiarity with MLOps platforms and cloud AI infrastructure.
• Strong collaboration with Digital/IT and governance stakeholders.

Responsibilities

• Define and maintain enterprise AI architectures and reusable patterns.
• Create AI design practices, review processes, and documentation standards.
• Update engineering standard work to reflect AI advancements.
• Define and maintain MLOps requirements and integration standards.
• Review subsystem designs for scalability and reuse.
• Mentor Embedded AI Architects and provide technical guidance.

Skills

Enterprise AI architecture

MLOps

Cloud AI infrastructure

Architecture standards

Governance & compliance

Education

Bachelor's degree in Engineering, Computer Science, Applied Mathematics, Data Science, or related field

Job description

GE Vernova is seeking a Senior AI Architect to define scalable AI architectures and enforce reusable patterns across Wind Engineering.

The role mentors Embedded AI Architects, drives AI standards, and partners with Digital/IT to establish MLOps and integration best practices for enterprise platforms. You will guide security, data governance, model risk, and quality management as AI capabilities expand across projects.