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# AI Architect Director - Agentic Systems

- **Company:** NTT DATA, Inc.
- **Location:** Dallas, TX, United States (Remote available)
- **Experience:** Expert
- **Salary:** $122,648.0 - $170,344.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Audit Trail, Microsoft Azure, Cluster Analysis, Customer Data Management, Python (Programming Language), Machine Learning, Azure Machine Learning, Fast Healthcare Interoperability Resources, Large Language Models, Multi-Agent Systems, Prompt Engineering, Data Lakes, AI Platforms, Information Technology, Health Level Seven International, Api Design, Automation Anywhere
- **Published:** June 9, 2026
- **Apply:** https://www.dice.com/job-detail/9ddbaf3b-17b4-46b9-8414-00530d699582

## About the Role

* 8+ Years of Strong experience in Python-based AI systems
 * 8+ Years of Hands-on experience with GenAI (LLMs, RAG, embeddings, prompt engineering)
 * 8+ Years of Experience with traditional ML (classification, regression, NLP, time-series)
 * 5+ Years of Full-stack experience (API design + UI integration)
 * 5+ Years of Azure cloud experience (Azure ML, Azure OpenAI, Functions, AKS)
 * 5+ Years of Experience working in regulated or compliance-heavy domains
 + Comfortable working with subject-matter experts
 + Strong learning mindset and adaptability
 + Experience building production AI systems, not just prototypes
 + Ability to explain AI decisions to non-technical stakeholders
 + Interest in agentic AI and next-generation AI architectures

Degree: Bachelors in Computer Science or equivalent work experience

Must reside in the US

## Description

* Design and implement agent-based AI workflows for different domains such as :
 + healthcare use cases (clinical assistants, triage agents, care pathway optimization, RCM automation)
 + Design agentic AI architectures for manufacturing workflows
 + Build multi-agent financial AI systems (analysis agents, compliance agents, advisory agents)
 + Implement RAG over financial documents, policies, contracts, and filings
 * Build LLM-powered systems (RAG, tool-calling agents, multi-agent orchestration)
 * Develop classical ML models (risk scoring, prediction, clustering, anomaly detection)
 * Implement HIPAA aware AI architectures with auditability and traceability
 * Implement GenAI systems using RAG over CRM, customer data, and content
 * Build full-stack applications (Python APIs, AI services, UI dashboards)
 * Integrate with EHRs, data lakes, and healthcare systems (FHIR/HL7 exposure preferred)
 * Integrate LLMs with sensor data, MES, ERP, and IoT platforms
 * Collaborate with SMEs to translate medical workflows into agent logic
 * Deploy, monitor, and optimize AI systems in Azure


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