AI Orchestration Engineer

Position Title: AI Orchestration Engineer

Department: Supply Chain Information Technology

Location: Atlanta, GA (Onsite Preferred) | Open to Remote – USA

About the Role

We are seeking a highly skilled AI Orchestration Engineer to join our customer’s 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 (e.g., LangChain, LangGraph, LangSmith, AutoGen, CrewAI, or custom), Temporal and Design required to automate Supply Chain IT workflows end-to-end. Oracle Agent Studio preferred.

Strong Oracle Cloud Procurement techno-functional expertise, including hands-on implementation experience across Oracle Fusion Procurement modules such as Purchasing, Self Service Procurement, Supplier Portal, Sourcing, Contracts, and Supplier Management.

·     Experience with AI agent orchestration and agent-to-agent architecture, including practical knowledge of agentic AI, multi-agent workflows, human-in-the-loop processes, and AI-enabled procurement automation use cases

·     Strong solutioning, architecture, and communication skills, with the ability to translate business requirements into scalable automated/agentic solutions, design integrations/process flows, and clearly communicate with business and technical stakeholders.

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·     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

Must-Have 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. Experience with Oracle AI Agent Studio preferred.

·     Proficiency with AI/LLM orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, Haystack, or equivalent. Temporal, design and build end to end Multi-Agent Orchestration.

·     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.