Agentic AI Architect for Multidomain GenAI Systems

NTT DATA, Inc.; Los Angeles (CA); On-site; USD 130,000 - 180,000; Full time

Job summary

NTT DATA is seeking an Agentic AI Engineer to join our team in Los Angeles, California. The role will design and build agentic AI systems across healthcare, finance, and retail domains, blending GenAI, ML, and systems engineering to create AI agents that interact with machines, data streams, and enterprise systems.

You will deploy, monitor, and optimize AI systems in Azure, collaborate with subject-matter experts to translate medical workflows into agent logic, and develop production-grade AI

Qualifications

• 8+ years of experience with Python-based AI systems.
• 8+ years hands-on GenAI experience (LLMs, RAG, embeddings, prompt engineering).
• Experience with traditional ML (classification, regression, NLP, time-series).
• Experience in regulated or compliance-heavy domains.

Responsibilities

• Design and implement agent-based AI workflows across domains such as Healthcare, Finance, and Retail.
• Create agentic AI architectures for manufacturing workflows.
• Build multi-agent financial AI systems (analysis, compliance, advisory).
• Implement RAG over documents, policies, contracts, and filings.
• Develop LLM-powered systems (RAG, tool-calling agents, multi-agent orchestration).
• Develop production ML models (risk scoring, prediction, clustering, anomaly detection).
• Implement HIPAA-aware AI architectures with auditability and traceability.
• Deploy, monitor, and optimize AI systems in Azure.

Skills

Python-based AI

GenAI / LLMs

Traditional ML

Regulated domains

SME collaboration

Production AI systems

Explainability

Agentic AI concepts

Education

Bachelor's in CS

Tools

Azure

Job description

NTT DATA is seeking an Agentic AI Engineer to join our team in Los Angeles, California. The role will design and build agentic AI systems across healthcare, finance, and retail domains, blending GenAI, ML, and systems engineering to create AI agents that interact with machines, data streams, and enterprise systems.

You will deploy, monitor, and optimize AI systems in Azure, collaborate with subject-matter experts to translate medical workflows into agent logic, and develop production-grade AI