AI Orchestration Engineer

Trident Consulting•Plano, TX

1d•Onsite

About The Position

Trident Consulting is seeking an AI Orchestration Engineer for one of our clients in Plano, TX. This role involves architecting and implementing AI orchestration frameworks to automate Supply Chain IT workflows, integrating these frameworks with enterprise systems, and deploying workloads on cloud infrastructure. The engineer will also be responsible for implementing observability, logging, and security standards for AI systems, and collaborating with business and IT stakeholders to identify and scope AI automation opportunities.

Requirements

Implemented in AI Tools prod and being used
Implementation experience in Oracle AI Agents studio, Lang Graph, Lang Chain and Lang Smith
Good Oracle Functional knowledge.

Responsibilities

Architect and implement multi-agent and single-agent AI orchestration frameworks (e.g., 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.
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.
Deploy orchestration workloads on cloud-agnostic infrastructure (AWS, Azure, or GCP) 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).
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.