ML Ops Enterprise Architect

Job Title: ML Ops Enterprise Architect

Rate: $50/hr-$60/hr

Location: - US Remote

Job Title: Enterprise Architect - ML/AI & Data Architecture

Job Summary

This horizontal role defines and governs technology strategy that supports multiple business units and domains across the organization. The Enterprise Architect acts as a critical link between business strategy and technology execution across the entire portfolio.

The role operates with broad autonomy and a high level of complexity under the guidance of senior team members. It influences executive decisions, shapes strategic technology roadmaps, and leads initiatives spanning multiple platforms and technologies.

The Enterprise Architect designs and develops IT architecture strategies, standards, and roadmaps while delivering Enterprise Architecture across integrated processes, applications, data, and technology in alignment with the organization''s Enterprise Architecture vision and direction.

This position requires specialized depth and/or breadth of expertise in Enterprise Architecture or a related field. The role interprets internal and external business challenges and recommends industry best practices to improve products, processes, and services.

Position Title: Enterprise Architect

Essential Job Functions

• Architect and implement scalable AWS ML/AI cloud infrastructure within a multi-tenant SaaS environment.
• Collaborate with Data Scientists, Data Engineers, and IT teams to define requirements, architecture standards, and best practices for ML model development, deployment, and monitoring.
• Evaluate and recommend tools, platforms, and cloud technologies for MLOps, ensuring alignment with enterprise architecture standards.
• Oversee the integration of ML pipelines with existing enterprise data and application architectures. Familiarity with Guidewire integrations is highly desirable.
• Oversee ML/AI-related Kubernetes cluster management and provide guidance on alternative ML/AI workflow orchestration solutions, such as Argo and Kubeflow.
• Design, manage, and govern ML/AI data pipelines using tools such as Apache Airflow.
• Leverage tools such as Argo CD to automate infrastructure deployment and management.
• Mentor and guide technical teams on MLOps architecture, tooling, standards, and best practices.

Experience Requirements

• Minimum of 10 years of experience across architecture disciplines, with significant experience in Enterprise Architecture leadership.

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