AI Solutions Architect

Position Summary The AI Solutions Architect serves as the technical leader and strategic advisor within the AI Center of Excellence (AI CoE). This individual will oversee all AI projects and initiatives across the enterprise, ensuring best practices are followed from ideation through production deployment. The role is responsible for maintaining a comprehensive map of every AI initiative, documenting integration points, and designing scalable solutions that align with business objectives. The AI Solutions Architect acts as the connective tissue between business stakeholders, engineering teams, and vendor partners, translating complex requirements into actionable architectures. Key Responsibilities AI Program Oversight & Governance Oversee all AI projects and initiatives across the organization, ensuring alignment with the AI CoE's strategic roadmap and enterprise architecture standards. Establish and enforce best practices, design patterns, and governance frameworks for AI solution development, deployment, and lifecycle management. Conduct architecture reviews for all new AI initiatives to validate technical approach, scalability, security, and compliance requirements. Define and maintain AI solution architecture standards including model serving, data pipelines, API design, and observability. Define and design AI skill files that follow standards set. Documentation & Initiative Tracking Create and maintain a comprehensive catalog of all AI projects, including status, ownership, technology stack, data sources, and business impact metrics. Develop and manage initiative mapping documentation that clearly illustrates relationships, dependencies, and shared components across AI projects. Produce Technical Requirements Documents (TRDs), architecture diagrams, and design specifications for each initiative. Maintain a living knowledge base that captures lessons learned, reusable patterns, and reference architectures for the AI CoE. Stakeholder Engagement & Solution Design Meet regularly with business stakeholders, product owners, and department leaders to gather requirements, understand pain points, and identify high-value AI opportunities. Translate business requirements into detailed technical solution designs, including data flow diagrams, system architecture, and integration specifications. Present solution proposals and architecture recommendations to senior leadership, clearly articulating trade-offs, timelines, and resource needs. Facilitate cross-functional design sessions and workshops to align technical and business teams on AI initiative scope and approach. Integration Architecture & Connectivity Own the master integration map across all AI projects, documenting every touchpoint between AI systems, enterprise platforms (Salesforce, Snowflake, ERP, etc.), and external services. Design and standardize integration patterns including API contracts, event-driven architectures, data synchronization strategies, and middleware configurations. Identify opportunities for shared services, reusable components, and platform consolidation to reduce duplication and accelerate delivery. Collaborate with infrastructure and platform teams to ensure integration points are secure, performant, and well-monitored. Technology Strategy & Innovation Evaluate emerging AI/ML technologies, platforms, and frameworks (e.g., Gemini, Vertex AI, LangChain, vector databases) and provide recommendations for adoption. Partner with the Agent Development team to ensure AI agents follow consistent architectural patterns and integration standards. Contribute to vendor evaluation and selection processes, including reviewing SOWs, conducting technical due diligence, and validating proof-of-concept results. Stay current on AI industry trends, security considerations, and regulatory developments relevant to AI deployments in retail and automotive sectors. Required Qualifications Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field; Master's degree preferred. 8+ years of experience in enterprise architecture, solutions architecture, or a senior technical role with a focus on AI/ML systems. Proven track record of designing and delivering large-scale AI/ML solutions in a complex, multi-platform enterprise environment. Deep understanding of AI/ML concepts including large language models, natural language processing, computer vision, and agentic AI architectures. Strong experience with cloud platforms (GCP, AWS, or Azure), data engineering (Snowflake, BigQuery), and modern API design (REST, GraphQL, event-driven). Demonstrated ability to create clear, comprehensive technical documentation including architecture diagrams, TRDs, and integration specifications. Excellent communication and stakeholder management skills with the ability to translate between technical and business audiences. Experience with enterprise integration platforms, middleware, and data orchestration tools. Preferred Qualifications Hands-on experience with Google Cloud Vertex AI, Gemini, or similar enterprise AI platforms. Familiarity with AI agent frameworks and multi-agent orchestration patterns. Experience with CI/CD pipelines (e.g., Harness), observability platforms (e.g., Dynatrace), and infrastructure-as-code practices. Knowledge of AI security, prompt injection mitigation, and responsible AI governance. Professional certifications in cloud architecture (GCP Professional Cloud Architect, AWS Solutions Architect) or AI/ML specializations. Experience with enterprise data platforms including Salesforce, ServiceNow, or ERP systems. Full-time employment only. No C2C (corp-to-corp) arrangements. #J-18808-Ljbffr