Principal AI Architect

BUILD A BETTER CAREER WITH MSC

Serving customers and our community starts with the best people doing their best work. That is precisely what we have created at MSC Industrial Supply Co. We are a leading North American distributor of metalworking and maintenance, repair, and operations (MRO), products and services. We offer more than 2 million products and have over 80 years of experience across dozens of industries.

We aim to execute our Built to Make You Better brand promise for all our stakeholders, including our associates.

Requisition  :21691

Employment Type :Full Time

Job Category :Digital/IT

Work Location :Melville, NY (CSC)

BRIEF

POSITION SUMMARY:

The Principal AI Architect serves as the principal technical design authority within the Enterprise Data Science & AI Center of Excellence (CoE). This role is responsible for architecting enterprise‑grade AI and agentic reference frameworks, defining the core technical foundations that support them, and leading the design and implementation of the company's knowledge and context infrastructure. The role serves as a critical cross‑functional bridge — partnering with architects across Information Security, Cloud Infrastructure, Data Platform, and Application Development to ensure enterprise-wide technical alignment.

The Principal AI Architect also guides technical delivery, working closely with data scientists, MLOps specialists, and AI developers to translate complex AI models into scalable, production‑grade enterprise software.

DUTIES AND RESPONSIBILITIES

• Technical Strategy & Roadmap: Own the technical roadmap for AI and agentic systems architecture, establishing the standards, patterns, and technical direction that guide AI solution design across the enterprise.
• Final Architectural Authority: Own final decision‑making authority on AI and agentic system architecture, resolving cross‑team technical conflicts and ensuring consistency across all AI initiatives.
• Reference Architecture & Standards:
  
  Define, maintain, and enforce enterprise‑wide AI reference architectures and technical quality evaluation baselines to ensure software reliability across all product teams.
• Sovereign Stack Design:
  
  Architect and maintain the secure, internal sovereign AI layered stack natively embedded inside enterprise Google Cloud Platform (GCP) and Azure tenants.
• Cross‑Architecture Partnership:
  
  Partner extensively with enterprise architects across
  
  Information Security, Cloud Infrastructure, Data Platform, and Application Development to ensure AI environments are seamlessly integrated, securely isolated, cost‑optimized, and compliant with broader infrastructure standards.
• Execution Team
  
  Collaboration:
  
  Set technical direction for data scientists, MLOps specialists, and AI developers by defining pipeline architecture, model deployment standards, and CI/CD quality gates. Conduct code reviews on key architectural components and integration points to ensure execution stays aligned with the broader AI system design.
• Semantic Context Layer Engineering:
  
  Design and build high‑fidelity unified metadata environments, semantic graphs, vector pipelines, and enterprise Knowledge Graphs to fuel reliable multi‑step agentic reasoning across functional boundaries.
• Model‑Agnostic Infrastructure Stack:
  
  Establish modular tech stack pathways that decouple application logic from foundational models, enabling engineering teams to seamlessly evaluate, swap, or cascade underlying large language models (LLMs) and small language models (SLMs) without vendor lock‑in.
• Modern Composable Core Integration:
  
  Collaborate with IT matrix teams to transition legacy technical debt into modern, API‑driven pathways and wrappers optimized for agentic tool calling and autonomous execution workflows.
• Tech‑Enabled Control Planes:
  
  Co…