AI Architect

Genius Business Solutions (GBSI); Plano (TX); On-site; USD 170,000 - 250,000; Full time

Job summary

Genius Business Solutions (GBSI) in Plano, TX is seeking an AI Architect to design, build, and operate AI orchestration pipelines that connect ERP, ITSM, and supply chain apps into intelligent, automated workflows.

You will bridge AI/ML capabilities with enterprise integration, delivering value across procurement, logistics, inventory, and fulfillment domains while ensuring security and compliance in a W2 environment requiring 14+ years of experience.

Qualifications

• Hands-on AI orchestration in production.
• Experience with Oracle/ServiceNow integrations.
• Python or Java/Node.js for integrations.

Responsibilities

• Architect and implement AI orchestration frameworks for SCM workflows.
• Design agentic pipelines interfacing with Oracle ERP, SNOW, and third-party platforms.
• Develop API gateways, event-driven connectors, and middleware for real-time data.
• Collaborate with Oracle and ServiceNow teams to expose APIs and data streams.
• Ensure data consistency and error handling across integrations.

Skills

AI orchestration

Enterprise integration

Python programming

REST APIs

Kafka / messaging

Tools

LangChain

LangGraph

Semantic Kernel

Docker

Kubernetes

Job description

Role: AI Architect
Location: Plano, TX
Only W2 accepted with 14+ years of experience.

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.