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AI Architect

Maven CompaniesDuluth, GA🇺🇸United StatesPosted 8 Sept 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Duluth, GA, United States
Posted
Yesterday
SQLMLOpsMLflowMachine LearningAzureDatabricksDeep LearningGenerative AIGoogle CloudPython

Job Description

Experience: 12+ Years

Job Summary: We are seeking an experienced AI Architect with strong expertise in the Retail industry to lead the design, development, and implementation of AI-driven solutions across enterprise SDLC. The ideal candidate will possess deep knowledge of AI/ML technologies, cloud platforms, retail business processes, and enterprise architecture.

Key Responsibilities:

  • Define and drive the AI strategy aligned with retail Tech organization objectives.
  • Architect scalable AI/ML solutions for retail use cases in the tech organization (SDLC):
  • Design and implement GenAI solutions such as:
  • Retail Chatbots & Virtual Assistants
  • Product Content Generation
  • Customer Service Automation
  • Knowledge Management Solutions
  • Work closely with stakeholders, product teams, and data scientists to identify and prioritize AI opportunities.
  • Develop enterprise AI architecture, MLOps frameworks, governance models, and deployment standards.
  • Build cloud-native AI solutions using Google Cloud Platform.
  • Experience in AI Platform development.
  • Establish AI governance, responsible AI practices, and model monitoring frameworks.
  • Evaluate emerging AI technologies and provide architectural recommendations.
  • Lead technical teams and mentor data engineers, ML engineers, and AI developers.

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.
  • 12+ years of IT experience with 5+ years in AI/ML solution architecture.
  • Strong retail domain experience
  • Hands-on experience with:
  • Machine Learning
  • Deep Learning
  • Generative AI
  • Large Language Models (LLMs)
  • RAG (Retrieval-Augmented Generation)
  • Agentic AI Frameworks
  • Experience with Python, SQL, Spark, and data engineering frameworks.
  • Expertise in cloud AI services:
  • Google Vertex AI
  • Strong knowledge of MLOps tools such as MLflow, Kubeflow, Databricks, or SageMaker.
  • Experience with vector databases (Pinecone, Weaviate, ChromaDB, Azure AI Search).

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