Role: AI Architect
Location: Plano,TX
Only W2 accepted with 14+ years of experience.
Please check the below JD and share the updated resume on
Job Summary
We are seeking a highly skilled AI Orchestration Engineer to join our Supply Chain IT organization. In this role, you will design, build, and operate AI orchestration pipelines that connect enterprise platforms — including Oracle ERP, ServiceNow (SNOW), and a broad ecosystem of supply chain applications — into intelligent, automated workflows. You will be the technical bridge between AI/ML capabilities and enterprise integration, ensuring orchestrated agents and models deliver real business value across procurement, logistics, inventory, and fulfillment domains.
Key Responsibilities
AI Orchestration & Pipeline Engineering
• Architect and implement multi-agent and single-agent AI orchestration frameworks (LangChain, LangGraph, AutoGen, CrewAI, or custom) to automate Supply Chain IT workflows end-to-end.
• Design agentic pipelines with tool-use, memory, and reasoning loops that interface with Oracle SCM/ERP, ServiceNow, and third-party supply chain platforms.
• Build and maintain prompt engineering strategies, chain-of-thought patterns, and retrieval-augmented generation (RAG) pipelines tuned for supply chain data and documents.
• Evaluate and select orchestration tooling and LLM providers (OpenAI, Anthropic, Azure OpenAI, Google Vertex AI, open-source) based on use case fit, performance, and cost.
Enterprise Integration
• Develop and maintain integrations between AI orchestration layers and enterprise systems including Oracle E-Business Suite / Oracle Cloud SCM, ServiceNow ITSM/ITOM, and WMS/TMS/MES platforms.
• Design and implement API gateways, event-driven connectors, and middleware (REST, SOAP, GraphQL, gRPC, Kafka, MQ) to feed real-time data into orchestration workflows.
• Collaborate with Oracle and ServiceNow platform teams to expose relevant APIs, webhooks, and data streams consumed by AI agents.
• Ensure data consistency, idempotency, and error handling across heterogeneous system integrations.
Platform & Infrastructure
• Deploy orchestration workloads on cloud-agnostic infrastructure (AWS, Azure, or Google Cloud Platform) using containerized services (Docker, Kubernetes) and serverless compute where appropriate.
• Implement observability, logging, tracing, and alerting for AI pipelines using tools such as LangSmith, MLflow, Datadog, or OpenTelemetry.
• Maintain security and compliance standards for AI systems handling supply chain data (PII, supplier data, inventory data).
Collaboration & Stakeholder Engagement
• Partner with Supply Chain business analysts, process owners, and IT architects to identify, prioritize, and scope AI automation opportunities.
• Translate business requirements into technical orchestration designs; document architectures, data flows, and integration specs.
• Mentor junior engineers and contribute to an internal center of excellence (CoE) for AI and automation within IT.
Required Qualifications
- 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.