AI Architect

Job Title : AI Architect

Location : Plano, TX

Job Description:

• Bachelor's degree or Master’s Degree in Computer science, or a related field, with minimum 10+ years of experience.
• 3+ years of hands-on AI orchestration experience — designing and operating agentic AI systems, LLM pipelines, or intelligent automation workflows in production environments.
• Proven enterprise integration experience — building integrations with Oracle (EBS, Oracle Cloud, Fusion SCM) and/or ServiceNow via REST/SOAP APIs, webhooks, or middleware platforms.
• Proficiency with AI/LLM orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, Haystack, or equivalent.
  Strong programming skills in Python (primary) and/or Java/Node.js for building integration and orchestration components.
• Experience with API design and consumption (REST, GraphQL, OpenAPI/Swagger) and message queuing systems (Kafka, RabbitMQ, Azure Service Bus, or similar).

Technical Skills:

• Cloud platforms: AWS, Azure, or Google Cloud Platform — platform agnostic, comfortable deploying on any major provider.
• Containerization and orchestration: Docker, Kubernetes (EKS/AKS/GKE), Helm.
• CI/CD and DevOps: Git, GitHub Actions, Azure DevOps, Jenkins, or equivalent.
• Data integration: Familiarity with ETL/ELT patterns, data pipelines, and supply chain data models (PO, ASN, inventory, demand signals).
• Monitoring and observability: Experience instrumenting AI workloads for production reliability. Preferred Qualifications
• Experience in Supply Chain IT, manufacturing, logistics, or distribution industry verticals.
• Familiarity with Oracle Integration Cloud (OIC), Oracle API Gateway, or MuleSoft / Dell Boomi / Informatica for enterprise iPaaS.
• Hands-on experience with ServiceNow Flow Designer, IntegrationHub, or Virtual Agent for AI-enhanced ITSM workflows.
• Knowledge of supply chain domain concepts: demand planning, inventory optimization, order management, 3PL/carrier integration, supplier portals.
• Experience with vector databases (Pinecone, Weaviate, pgvector) and RAG architectures for enterprise document intelligence.
• Exposure to AI governance, responsible AI practices, and enterprise LLM security (prompt injection, data leakage prevention).
• Relevant certifications: AWS Solutions Architect, Azure AI Engineer, Google Professional ML Engineer, or Oracle Cloud Infrastructure