Define the enterprise AI architecture strategy, ensuring understanding of IT modernization and digital transformation goals.
Design scalable AI/ML platforms, pipelines, and integration patterns spanning cloud, on-premises, and hybrid environments.
Partner with business and IT leaders to translate organizational goals into AI solution designs with measurable outcomes.
Lead the architecture and governance of data, models, and AI services, ensuring compliance with cybersecurity, data privacy, and regulatory requirements.
Establish standards for AI pipeline development, model deployment, and lifecycle management within enterprise systems.
Collaborate with infrastructure, data engineering, and application teams to integrate AI capabilities into ERP, analytics, and business process ecosystems.
Recommend AI tools, platforms, and frameworks that align with existing enterprise architecture standards (e.g., Microsoft Azure, Oracle, SAP).

Requirements

8+ years of progressive IT experience, including 3+ years in AI/ML solution design or enterprise architecture.
Experience architecting and deploying AI solutions in cloud environments (Azure, AWS, or Google Cloud).
Enterprise systems knowledge—ERP, data warehousing, analytics, or workflow automation platforms.
Experience applying AI for business transformation, optimization, and workforce enablement in large organizations.
Background in regulated or critical-infrastructure environments (e.g., energy, utilities or manufacturing) desirable.
Certifications in AI or Cloud Architecture (Azure AI Engineer, Data Engineer.)
Understanding of AI/ML frameworks, MLOps principles, and data architecture best practices.
Grasp of cybersecurity, data privacy, and AI governance principles.
Advanced programming skills in Python, SQL, and knowledge of data engineering frameworks.
Proficiency in cloud AI platforms (Azure AI, AWS Sagemaker, or GCP Vertex AI).

Benefits

Comprehensive Health and Income Protection Benefits
401(k) Savings Plan
Paid Vacations for Qualifying Positions

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

AI architectureAI/ML solution designAI pipeline developmentmodel deploymentdata architectureprogramming in PythonSQLMLOps principlescloud AI platformsdata engineering frameworks

Soft skills

collaborationleadershipcommunicationorganizational skillsstrategic thinking

Certifications

Azure AI EngineerData Engineer