Senior Solution Architect, AI

JOB SUMMARY:

The Sr. Solution Architect (AI Specialty) is responsible for strategically designing enterprise-grade application and AI solution architectures that support global, multi-park operational needs while also accommodating tailored requirements for individual parks. This role emphasizes modernizing digital platforms and applications through the integration of Artificial Intelligence (AI), Machine Learning (ML), Computer Vision (CV) and intelligent automation solutions. This role will play a pivotal role in the design of AI-driven systems, next-generation platforms, and cloud-native applications across the UDX global portfolio — with a focus on AI use cases such as predictive analytics, personalization, operational optimization, computer vision, and natural language processing (NLP).

MAJOR RESPONSIBILITIES:

Strategy & Planning

• Act as a visionary and strategist for AI-centric and intelligent solutions within the enterprise application and technology portfolio. Assist in the development of long-term strategic goals and short-term tactical plans for the integration, management, and scaling of Computer Vision, AI and machine learning (ML) capabilities. Ensure proposed and existing AI solution architectures align with Data Architecture, Enterprise Architecture, and Responsible AI guidelines.
• Provide architectural expertise, thought leadership, and direction to delivery teams, DevOps engineers, AI/ML engineers, and fellow architects. Develop, document, and communicate AI-enabling strategies, roadmaps, and investment plans — including cost-benefit analysis for AI adoption opportunities, risk assessment, and model lifecycle management strategies.
• Conduct ongoing research and evaluation of emerging technologies, platforms, and frameworks in support of business and systems development efforts. Recommend intelligent automation, predictive analytics, personalization, and operational optimization solutions to enhance enterprise capabilities and business value.

Solution Design

• Architect, design, and oversee the implementation of enterprise AI-enabled solutions and intelligent applications across operational and customer-facing domains. Serve as the AI architecture domain expert for development, data, and ML engineering teams during solution design and implementation phases.
• Document and maintain the organization's AI-related solution architecture portfolio and technology ecosystem. Influence the strategic direction by delivering AI-specific design patterns, model integration frameworks, and platform capabilities that demonstrate the art of the possible for data-driven and AI-enhanced solutions.
• Review and provide architectural oversight on AI use case solutions and intelligent application designs proposed by other architects. Ensure alignment with AI best practices, security, privacy, model governance, industry standards, and architectural standard operating procedures (SOPs).

Technical Collaboration

• Collaborate with delivery teams, product managers, AI/ML engineers, and senior leadership to refine AI-related business requirements and solution objectives. Participate in the identification, prioritization, and technical feasibility assessment of AI opportunities across business units.
• Work with cross-functional teams to translate business objectives into AI/ML solution requirements, technical designs, and deployment strategies. Engage with other architects and domain experts through solution review boards to evaluate AI solution proposals, review model governance protocols, and assess AI security, ethics, and privacy implications.
• Provide expert guidance on technical AI/ML issues, platform integration challenges, and AI model lifecycle management considerations, including MLOps, data pipeline design, retraining strategies, and AI model monitoring.
• Understands and actively participates in Environmental, Health & Safety responsibilities by following established UO policy, procedures, training and team member involvement activities.
• Performs other duties as assigned.

EDUCATION:

Bachelor's Degree in Computer Science, Computer Engineering, Systems Engineering or similar essential required.

EXPERIENCE:

• 9+ years of IT experience with large integrated projects; or equivalent combination of education and experience.
• 3+ years of hands-on experience designing and implementing AI/ML solutions within enterprise or large-scale operational environments.
• Repeatedly demonstrated ability to produce requirement artifacts: data flow diagrams, UML modeling techniques include sequence, component, deployment and domain models.
• Proven experience architecting AI/ML model integration into enterprise applications and operational systems.
• Experience working with cloud-based AI/ML services and platforms (AWS SageMaker, Azure Machine Learning, etc.) and containerized deployment of AI workloads.
• Strong familiarity with AI/ML frameworks and integration patterns for model inference, retraining, and monitoring.
• Experience leading AI model lifecycle management (MLOps), including CI/CD pipelines for AI models, model versioning, and operational monitoring.
• Demonstrated experience in AI security, privacy, ethical AI practices, and model governance frameworks.
• Experience collaborating with data architects, data scientists, AI/ML engineers, and cloud platform teams to deliver integrated AI solutions.
• Strong background in application modernization, microservices, event-driven architectures, and API management.
• Experience developing and maintaining AI and intelligent solution architecture standards, patterns, and reusable assets.
• Proven track record evaluating AI vendor solutions, third-party APIs, and AI marketplaces for enterprise adoption.
• Experience conducting technical risk assessments and AI feasibility studies for proposed AI initiatives.
• Demonstrated ability to translate business use cases into AI/ML solution designs, considering data availability, model suitability, and operational constraints.
• Solid experience with enterprise architecture frameworks (TOGAF, Zachman, or similar) and architectural review boards.
• Excellent communication, presentation, and stakeholder management skills, including experience advising senior business and technology leaders on AI strategy and adoption.
• Experience leading technical design sessions, solution review boards, and architecture governance processes for AI initiatives.
• Strong background in technical documentation, architectural diagrams, workflow modeling, and AI solution roadmapping.

Your talent, skills and experience will be rewarded with a competitive compensation package.

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