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Ai In Jobs in Atlanta, TX (NOW HIRING)

... in Prompt Engineering (Zero/Few-shot, Chain-of-Thought) and prompt design. • Strong Python ... Roles & Responsibilities 1) Architecture & Strategy (AI / Agentic AI) • Define the overall ...

We do not use artificial intelligence (AI) tools to make hiring decisions, and we ask that candidates disclose any use of AI in the application and interview process. Disclaimer: Applicants must be ...

Houston, TX or Boston, MA (Hybrid 2 Days in Office) Reports to : VP, AI Engineering, AI Platform A quick snapshot... As a Staff Data Scientist, you will be a key technical leader responsible for ...

We do not use artificial intelligence (AI) tools to make hiring decisions, and we ask that candidates disclose any use of AI in the application and interview process. CBRE is an equal opportunity ...

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Ai In information

What is the difference between Ai In vs Data Analyst?

AspectAi InData Analyst
Required CredentialsTypically a degree in AI, computer science, or related field; certifications in AI or machine learningDegree in statistics, mathematics, or related field; certifications in data analysis or visualization
Work EnvironmentTech companies, AI research labs, startups; focus on developing AI modelsBusiness, finance, healthcare sectors; analyze data to inform decisions
Employer & Industry UsagePrimarily in tech and AI-focused industriesAcross various industries including finance, healthcare, marketing

While both roles involve working with data, Ai In focuses on developing and implementing AI models, whereas Data Analysts interpret data to support business decisions. Ai In roles require specialized knowledge in AI and machine learning, while Data Analysts focus on data visualization and statistical analysis.

What cities near Atlanta, TX are hiring for Ai In jobs?

Cities near Atlanta, TX with the most Ai In job openings:

Infographic showing various Ai In job openings in Atlanta, TX as of June 2026, with employment types broken down into 2% As Needed, 93% Full Time, 3% Part Time, and 2% Temporary. Highlights an 69% Physical, 3% Hybrid, and 28% Remote job distribution.

Full-time

Posted 5 days ago


Job description

Job title: AI Architect
Role is onsite
Client address:
2900 W Plano Pkwy Plano, TX 75075
Years of experience required: 12+y
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.
Job Description:
• AI Orchestration & Pipeline Engineering • 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. 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 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). 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. • 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 GCP - 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
Years of Experience: 14.00 Years of Experience
Regards
danyal
danyal@rurisoft.com