AI Solution Architect

Ports North; Lincolnshire (IL); On-site; USD 120,000 - 160,000; Full time

Job summary

Ports North is seeking an experienced AI Solutions Architect to lead the technical strategy in their internal AI Center of Excellence. This role includes overseeing AI initiatives across the enterprise, establishing best practices, and maintaining a comprehensive catalog of AI projects.

Ideal candidates will have over 8 years of experience in enterprise architecture focusing on AI/ML, strong cloud platform knowledge, and excellent communication skills to liaise with stakeholders and engineering teams.

Qualifications

• 8+ years of experience in enterprise architecture or AI/ML systems.
• Proven track record of delivering large-scale AI solutions.
• Strong experience with data engineering and API design.

Responsibilities

• Oversee AI projects ensuring alignment with strategic roadmap.
• Conduct architecture reviews for AI initiatives.
• Translate business requirements into technical solutions.

Skills

AI/ML concepts

Cloud platforms (GCP, AWS, Azure)

API design (REST, GraphQL)

Technical documentation

Stakeholder management

Education

Bachelor's degree in Computer Science or related field

Master's degree preferred

Tools

Google Cloud Vertex AI

Snowflake

CI/CD tools (e.g., Harness)

Job description

AI SOLUTIONS ARCHITECT

Our client is seeking an experienced AI Solutions Architect to serve as the technical leader and strategic advisor within the internal AI Center of Excellence (AI CoE). You will oversee all AI projects and initiatives across the enterprise, ensuring best practices are followed from ideation through production deployment. The AI Solutions Architect is responsible for maintaining a comprehensive map of every AI initiative, documenting integration points, and designing scalable solutions that align with business objectives. You will be the connective tissue between business stakeholders, engineering teams, and vendor partners, translating complex requirements into actionable architectures.

Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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.

Requirements

• 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.
• 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.