AI Enterprise Architect:

The AI Enterprise Architect assists the Principal Architect during Professional Services engagements and collaborates with Lead or Principal consultants and other cross-functional teams on complex customer projects focused on AI technologies, particularly those involving NVIDIA solutions. The AI Enterprise Architect is a technical and business outcome leader who provides oversight and alignment between WWT Engineers, Architects, and the customer's technical or business leaders for AI-centric projects.

The AI Enterprise Architect may be assigned to lead customer-facing services projects of varying size and complexity, often including the development of AI-specific project deliverables (examples include white papers, plans, strategies, designs, assessments, and business case analyses). When designated as the Solution / Technical leader, they will combine with PMO leadership to form the "Two in the Box" model, a vital part of WWT's approach to driving successful AI project outcomes.

• Client Scope and Objectives: The AI Enterprise Architect understands all client scopes and objectives related to AI technologies. They serve as the primary technical voice facing the client externally and the escalation point internally for WWT employees, Partners, and Contractors.
• Risk and Issue Resolution: Partner with the PMO counterpart to identify and resolve risks and issues, leveraging a strong background in AI and the resources available within WWT.
• Best Practices and Templates: Ensure that WWT's best practices and templates for AI projects are followed and delivered to the customer.
• Technical Reviews: Review deployment documents, technical assessments, and other outputs to ensure consistent and accurate delivery, as defined by "One Voice.
• Project Management: Manage AI projects as if they were their own stand-alone business, focusing on profitability and professionalism.

• Customer Contact: Act as the technical and business contact between WWT and the customer from the beginning to the end of AI projects, ensuring the team meets the customer's desired outcomes.
• Architecture Activities: Demonstrate the ability to carry out architecture activities and methodologies leading to comprehensive discovery, analysis, and technical/business recommendations focused on AI solutions.
• Communication Skills: Exhibit advanced communication skills, including business/technical writing and presentations, especially related to AI technologies.
• Technical Presentations: Present in-depth technical AI solutions effectively.
• Project Team Motivation: Self-motivated with the ability to motivate and energize a project team towards AI-related goals.
• Customer and Project Goals: Drive to exceed customer and project goals, with a focus on AI technologies.
• Thought Leadership: Provide thoughtful leadership and innovative thinking in AI.
• Customer Service: Maintain a positive customer service attitude.
• Project Delivery: Ensure the delivery of project work, ongoing quality, adherence to standards, and appropriate resource allocation for current and future AI project demands.
• Client Relationships: Foster long-term client relationships with a proven track record of customer focus.
• Project Architectural Principles: Possess expert knowledge of AI project architectural principles and practices.
• Travel Requirements: Willing to travel 50-75% of the time.
• Problem Solving: Proactively detect technical deficiencies in AI projects and develop practical, workable solutions.
• Critical Task Execution: Take full responsibility for the overall execution and delivery of critical AI tasks or projects.

• Vision Communication: Convey the WWT vision in accurate and relevant terms, helping others see improvements through AI technologies.
• Strategic Priorities: Stay focused on department and WWT strategic priorities, allocating time and resources accordingly.
• Coaching and Mentoring: Demonstrate the ability to coach and mentor team members, especially in AI technologies.
• Technical Knowledge Expansion: Proactively seek ways to expand technical knowledge in AI.
• Professional Maturity: Possess professional maturity and presence, acting as a technical expert in AI.
• Industry Trends: Maintain current knowledge of industry trends and tools in AI to provide best-practice insight and recommendations.
• Regulatory Compliance: Ensure all components and usage are consistent and compliant with applicable standards, policies, and guidelines.

• Certifications: An AI Enterprise Architect should have industry-recognized enterprise architecture certifications such as TOGAF, Zachman, or specific AI and machine learning certifications.
• Experience: Minimum of five years (5) of industry experience in enterprise IT management, technology consulting, advisory, or professional services, with a focus on AI technologies.
• Consulting Experience: 3-5 years of experience as a Senior or Lead Consultant or equivalent experience in AI.
• Preferred Knowledge:
• Thorough understanding of AI technologies, especially NVIDIA solutions, and market trends.
• Post-graduate training in business-related disciplines or management.
• Advanced client-facing skills, including analyzing complex AI-related problems and influencing and negotiating with clients.
• Demonstrated technical consulting experience in sectors such as government, public sector, higher education, finance, healthcare, technology, or other commercial fields.