Description

Key Skills: Enterprise Architecture, AI Platforms, Machine Learning, Data Architecture, Solution Architecture, Enterprise Data Platforms, Analytics Solutions, AI Integration, Architecture Strategy, Platform Architecture

Good to Have Skills: Experience with Enterprise Architecture repository or modeling tools (LeanIX, Ardoq), real-time inference integrations, batch model processing, API-based model access, enterprise security concepts, secure model access, identity-based access, retail or consumer products experience, global teams collaboration, offshore delivery teams experience, distributed product and engineering organizations.

Roles & Responsibilities:

• Contribute to enterprise architecture strategy and support roadmap execution across enterprise AI and intelligent automation platforms
• Support development and adoption of reference architectures and standards for AI platforms, ML lifecycle solutions, and AI-enabled applications
• Lead architecture design and solution alignment for assigned AI, machine learning, or intelligent automation initiatives
• Partner with senior architects, engineering teams, and data science teams to ensure consistent AI platform and solution architecture design
• Support adoption of modern AI patterns including predictive analytics, real-time decisioning, and AI-enabled business workflows
• Participate in architecture reviews and provide architecture guidance to engineering, data engineering, and data science teams
• Contribute to AI platform evaluation, vendor selection, and AI solution modernization initiatives
• Demonstrate strong ownership of architecture deliverables and continuous improvement of architecture practices

Experience Required: Progressive experience working across enterprise architecture, solution architecture, data platform architecture, or AI/analytics platform environments. Demonstrated experience contributing to enterprise architecture, analytics platform, or AI solution modernization initiatives. Strong experience working within enterprise data, analytics, or AI-enabled platform architecture environments.

Education: Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or related field (Master's preferred)

Key Skills

Education

Any Graduate