AI Enterprise Solutions Architect

MUST be able to go on-site in Wilmington, DE as needed! This role ensures architectural governance over AI/ML initiatives and delivers measurable business value across global operations. The Enterprise Architect - AI/ML leads through influence and collaboration with domain architects, data scientists, and senior leaders, driving enterprise-wide AI innovation and operational excellence. Role & Responsibilities Strategic Leadership and Vision Define and evolve the enterprise AI/ML architecture vision aligned with the clients business strategy, goals, and target operating cost, including cloud-first AI strategies, vertical integration, and platform-led operating models. Champion Responsible AI (RAI) frameworks and governance , ensuring AI deployments are ethical, transparent, explainable, and compliant with the clients RAI principles and emerging regulations. Lead architectural oversight of AI/ML initiatives across domains (manufacturing, logistics, finance, enterprise functions, marketing, sales, commercial operations), ensuring strategic alignment and scalability. Define the AI/ML technology roadmap , including reference architectures for Retrieval-Augmented Generation (RAG), large language models (LLMs), computer vision, predictive analytics, and intelligent automation. Serve as the enterprise authority on AI/ML design patterns , including model lifecycle management (MLOps), feature stores, model registries, and inference pipelines. Operational Excellence Manage architecture documentation and AI model cataloging within enterprise platforms (eg, LeanIX ), ensuring lifecycle tracking and stakeholder visibility. Establish and enforce AI/ML standards, principles, and guardrails across all IT domains, embedding ARB checkpoints into AI development and deployment pipelines. Lead the Architecture Review Board (ARB) review process for all AI/ML-related technology selections, ensuring no AI capability is introduced without architectural accountability. Define reusable AI/ML reference architectures and patterns (eg, RAG pipelines, AI agent frameworks, model-as-a-service) to accelerate adoption and reduce fragmentation. Ensure AI/ML solutions meet security, data privacy, and compliance requirements, including alignment with Zero Trust and identity architecture standards. Stakeholder Engagement & Advisory Act as an internal consulting resource for AI/ML road-mapping, advising business leaders on AI-driven transformation opportunities aligned with 3-year business objectives. Partner with data engineering, data science, and platform teams to ensure AI/ML workloads are production-ready, scalable, and governed. Evangelize AI capabilities and best practices across the enterprise through communities of practice, lunch-and-learns, and executive briefings. Support M&A and divestiture activities by assessing AI/ML technology stacks and integration risks. Governance & Compliance Operationalize Responsible AI governance , including bias monitoring, model explainability, audit trails, and AI risk assessments. Introduce formal Architecture Exception Management for AI/ML deviations-time-bound, risk-accepted, and tracked. Ensure compliance with global AI regulations (eg, EU AI Act) and internal client policies. Required Qualifications 10+ years of enterprise architecture or solution architecture experience, with 5+ years focused on AI/ML architecture and strategy. Proven experience designing and deploying MLOps pipelines , model governance frameworks, and AI reference architectures at enterprise scale. Strong understanding of Responsible AI principles , including fairness, transparency, explainability, and accountability. Experience with cloud-first architectures (Azure, AWS, GCP) and data platforms supporting AI/ML workloads. Working knowledge of TOGAF or equivalent EA frameworks. Excellent communication skills with the ability to influence C-level stakeholders and translate technical AI concepts into business outcomes. Preferred Qualifications Experience with LeanIX or equivalent EA management platforms. Familiarity with SAP BTP , integration middleware, and ERP ecosystems in manufacturing contexts. Experience with RAG architectures , agentic AI patterns, and generative AI governance. Background in manufacturing or industrial sectors preferred. TOGAF certification, AI/ML professional certifications (eg, Azure AI Engineer, AWS ML Specialty). Compensation $80/hr to $90/hr. Exact compensation may vary based on several factors, including skills, experience, and education. Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.