Principal Architect - AI

About the role

The role of the AI Architect is to shape the organization's AI/ML strategy and roadmap, define AI/ML technical capabilities, establish AI reference architecture, standards, and best practices, lead integration of AI/ML into business system transformation initiatives, ensure consistency with organizational goals and technical standards, champion ethical AI governance and regulatory compliance, support continuous technology improvement and adaptable architecture, develop reusable AI/ML architectural patterns, operationalize AI use cases, evaluate emerging technologies, and mentor cross-functional teams.

Responsibilities

• Defines future state AI/ML architecture and technology roadmap.
• Links business strategies and processes to AI/ML technology strategies, ensuring AI initiatives support enterprise objectives and deliver measurable business value.
• Establishes and maintains models of AI-driven organizational value streams, goals, strategies, capabilities, processes, information, and IT assets.
• Ensures these models capture both traditional and AI/ML-specific business functions.
• Defines and enforces target state and reference architectures, principles, guardrails, and standards for AI/ML, ensuring alignment with industry best practices, ethical frameworks (e.g., responsible AI), and regulatory guidelines (GDPR, NIST AI RMF).
• Develops and manages AI governance frameworks including model lifecycle management (MLOps), model monitoring, data governance, bias mitigation, explainability (XAI), and compliance.
• Leads initiatives around AI governance, MLOps pipeline optimization (monitoring/drift detection), and continuous improvement of intelligent solutions.
• Develops and promotes reusable AI/ML architectural patterns (e.g., generative AI workflows, RAG architectures) that foster innovation while adhering to best practices.
• Collaborates with stakeholders to operationalize AI use cases (e.g., demand forecasting, NLP for customer service), embedding AI into end-to-end business process models.
• Led reviews of AI-driven solution designs for scalability, interoperability, and compliance.
• Investigates emerging technologies (agentic AI, genAI), assess enterprise impact through research/proof-of-concepts, and build business cases for adoption.
• Defines data requirements for AI (feature stores, pipelines), advises on data-sharing strategies to support ML models, and ensures data quality/security in AI contexts.
• Evaluates public cloud services and hybrid architectures for cost-effective deployment of intelligent systems.
• Mentors cross-functional teams on AI/ML adoption; bridge gaps between data scientists, engineers, and business units to foster a collaborative environment.

Requirements

• Exceptional executive presence and strong communication skills to translate technical concepts for executives and technical teams.
• Strong understanding and passion for emerging technologies.
• Proven skills in leadership, relationship building, negotiation, collaboration, advocacy, governance, and consensus building.
• Excellent verbal and written communication skills at all levels.
• Team player with proven ability to work effectively within a large matrix organization.
• Ability to make architecture changes in a dynamic agile environment.

Qualifications

• 5+ years' architecture experience with business/capability modeling using EA frameworks (TOGAF/Zachman).
• 5+ years of demonstrated experience with analyzing and documenting business value streams, capabilities, processes, and data using model-based representations for the purpose of collecting, aggregating, or analyzing complex business information.
• Proven ability to define future architecture/technology roadmap and align technology strategy with business goals.
• Bachelor degree or equivalent experience in computer science, information systems or related fields.
• Advanced degree a plus.
• 10+ years of Technology and Retail / Supply Chain experience.
• Experience working in ERP and Retail systems software (IBM i and/or SAP), including knowledge of Product Lifecycle.
• Knowledge of software development lifecycle methodologies with experience in both Classic and Agile (scaled) methodologies.
• Experience with distributed Enterprise/Solution Architecture.
• TOGAF certification, Cloud, AI certification.
• Working knowledge of DevOps, agile methodology, and continuous improvement.
• Industry AI publications/voice in leading forums.
• Proficient in Google Workspace applications, including Sheets, Docs, Slides, and Gmail.

Skills

• Hands-on with frameworks such as TensorFlow/PyTorch.
• Experience designing MLOps pipelines (MLflow/Kubeflow) and implementing model lifecycle management/governance.
• Knowledge of responsible/ethical AI practices: bias detection/mitigation; explainability; regulatory compliance.
• Proficiency in public cloud AI services: GCP Capgemini/Vertex AI.
• Knowledge of distributed data platforms (data lakes/feature stores).
• Experience with emerging AI and ML technologies to support the development of new solutions, such as, Agentic AI, GenAI, etc.

Benefits

Comprehensive benefits package including paid time off, health benefits, health care reimbursement account, dependent care assistance plan, short-term disability and long-term disability insurance, AD&D insurance, life insurance, 401(k), stock purchase plan to eligible employees.