AI Solutions Architect – Enterprise Back-End Systems

This is a remote position.

Job Title: AI Solutions Architect – Enterprise Back-End Systems

About the Role

We are seeking an experienced AI Solutions Architect to lead the design, governance, and delivery of AI-driven and intelligent automation solutions across enterprise back-end systems.

This role focuses on integrating AI capabilities into core platforms such as CRM, ERP, and iPaaS, ensuring scalable, secure, and business-aligned implementations.

Key Responsibilities

• Design and implement AI-driven solutions across enterprise systems (CRM, ERP, iPaaS)
  
• Define architecture for integrating AI/ML capabilities into backend workflows
  
• Lead system integration using APIs, event-driven architectures, and automation pipelines
  
• Collaborate with business and technical teams to align AI solutions with organizational goals
  
• Ensure scalability, security, and governance of AI systems in production environments
  
• Communicate architectural decisions clearly to stakeholders and leadership
  
• Drive end-to-end delivery aligned with enterprise technology standards
  

Requirements

Required Skills & Experience

• 10+ years of experience in enterprise architecture, system integration, or similar roles
  
• Strong experience with at least one platform in each category:
  
  • CRM: Salesforce, HubSpot, or Microsoft Dynamics 365
    
  • ERP: SAP S/4HANA, Oracle ERP, or NetSuite
    
  • iPaaS: MuleSoft, Boomi, Workato, or Azure Integration Services
    
• Hands-on experience implementing AI/ML solutions in production, such as:
  
  • LLM-powered workflows
    
  • Agentic AI systems
    
  • Predictive analytics
    
  • Intelligent document processing
    
• Strong understanding of integration patterns: REST/GraphQL APIs, event streaming, ETL/ELT, webhooks
  
• Excellent communication skills to work with both technical and non-technical stakeholders
  
  

Preferred Qualifications

• Experience with vector databases and RAG (retrieval-augmented generation) architectures
  
• Familiarity with AI governance frameworks (e.g., NIST AI RMF, EU AI regulations)
  
• Knowledge of data privacy, security, and secure development practices
  
• Cloud certifications (AWS, Azure, or GCP)
  
• Experience in regulated industries such as financial services, healthcare, or manufacturing
  

Benefits