This role blends strategic architecture leadership, deep technical expertise, and cross functional influence. You will define company’s target-state architecture across major platforms—eCommerce, ERP, CRM, contact center, data/AI, pricing systems—and ensure the enterprise evolves from legacy, point2point integrations toward a composable, event driven, API-first environment that unlocks enterprise-wide AI reuse and accelerates value delivery.

Essential Duties And Responsibilities

 Enterprise Architecture Strategy & Vision

Define and implement Company’s AI-centric target-state architecture spanning:

eCommerce & digital experience platforms

ERP systems including Epicor P21, NetSuite

CRM (Salesforce)

Contact center (Genesys Cloud)

Demand planning, Pricing, inventory, forecasting, and fulfillment intelligence platforms

Enterprise Data & AI Platforms (streaming, feature stores, data pipelines, MLOps)

Domain Driven Architecture and Micro Services Architecture

Develop multiyear roadmaps that modernize Company’s application ecosystem while enabling AI powered workflows across commercial, operational, and finance domains.

 Integration Modernization & Platform Evolution

Lead the transformation from point2point / batch integrations to a composable, service-based, event-driven, and API-first architecture.

Establish enterprise integration standards—event schemas, API guidelines, synchronous/asynchronous communication patterns, and governance models.

Ensure all platforms can seamlessly consume and contribute to reusable AI services, enabling shared intelligence across channels (web, sales, operations, fulfillment, support).

 AI/ML Architecture & Reference Designs

Define enterprise grade reference architectures for AI/ML use cases including:

Pricing optimization (dynamic pricing, elasticity, competitive intelligence)

Demand forecasting

Recommendations and personalization

Lead scoring & sales intelligence

Email and document intelligence (classification, extraction, anomaly detection)

Operational anomaly detection & predictive quality

This Includes Standards And Architectures For

Data/feature pipelines and ingestion orchestration

Online/offline feature stores

Real-time streaming architectures

Model deployment patterns across MLOps/ModelOps/LLMOps frameworks

 Platform Governance, Security, & Risk Management

Define architecture guardrails ensuring all AI-enabled systems are secure, governed, monitored, and compliant.

Establish reference patterns for securely embedding AI into transactional systems (ERP/CRM/contact center) while ensuring robustness, reliability, and traceability.

Partner with InfoSec to enforce API security, identity, secrets management, encryption, and policy controls.

 Data Quality, MDM, and Data Governance Leadership

Champion data quality, Master Data Management, and data governance as critical prerequisites for trustworthy AI and analytics.

Define system-of-record boundaries, governance processes, and ownership models for key enterprise data domains (product, customer, supplier, inventory, pricing, transactions).

Partner with the Data & AI teams to ensure feature quality, lineage, and observability.

 Cross-Functional Collaboration & Influence

Collaborate deeply with Product, Data, Security, Operations, eCommerce, Sales/ISR/OSR, Finance/AR, Procurement, and Executive stakeholders.

Translate business needs into architectural strategies that drive:

Customer experience improvements

Revenue growth and margin expansion

Operational efficiency and automation

Scalability and technical resilience

 Architecture Governance & Leadership

Lead architectural reviews, guiding teams toward target-state standards.

Provide mentorship to engineering and architecture teams; ensure architecture documents, decision logs, and diagrams are maintained.

Evaluate emerging technologies and frameworks relevant to Company’s future-state architecture.

Qualifications

Ability to align diverse stakeholders across business, product, and technology.

Excellent communication and the ability to convey complex architectural concepts simply.

Proven experience modernizing legacy integrations into API-first architectures.

Experience working in organizations undergoing digital and AI transformation similar to Company’s trajectory.

Knowledge & Skills Required

Deep knowledge of Data architecture & analytics, AI/ML architecture, and MLOps.

Deep knowledge of cloud platforms, microservices, distributed systems, and security architecture.

Experience architecting across ERP, CRM, eCommerce, and data platforms at enterprise scale.

Familiarity with GenAI platforms and frameworks (LangChain, CrewAI, LangGraph, vector search, RAG).

Prior involvement designing enterprise data governance frameworks and MDM.

Experience with Epicor P21, NetSuite, Salesforce, Genesys Cloud.

Education & Experience

High School Diploma or equivalent required

12+ years in Enterprise Architecture, Solution Architecture, or similar leadership roles.

Experience in industrial distribution, MRO, manufacturing, or supply chain domains.

Architecture certifications (TOGAF, Azure Solutions Architect) is a plus.

PHYSICAL DEMANDS

Continuous sitting and typing for extended periods.

Lifting requirements include occasional lifting of up to 25 pounds

Frequent walking or standing may be required at times