Agentic AI Engineer: GenAI & Multidomain Architect

Talentify; Los Angeles (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

NTT DATA is seeking an Agentic AI Engineer to join our team in Los Angeles, CA. You 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 and data streams.

Responsibilities include designing agent-based workflows, building multi-agent and RAG-enabled architectures, deploying on Azure, and collaborating with SMEs to translate medical workflows into agent logic.

Qualifications

• 8+ years of experience with Python-based AI systems.
• 8+ years hands-on experience with GenAI (LLMs, RAG, embeddings).
• Experience with traditional ML (classification, regression, NLP, time-series).
• Full-stack experience (API design + UI integration) – 5+ years.
• Azure cloud experience (Azure ML, Azure OpenAI, Functions, AKS) – 5+ years.
• Experience in regulated domains and ability to work with SMEs.

Responsibilities

• Design and implement agent-based AI workflows for different domains (healthcare, finance, retail).
• Build multi-agent financial AI systems (analysis, compliance, advisory).
• Implement RAG over documents, policies, contracts, and filings.
• Develop GenAI systems with LLMs, tool-calling, and orchestration.
• Deploy and monitor AI systems in Azure; ensure HIPAA-compliant architecture.

Skills

Python-based AI systems

GenAI (LLMs, RAG, embeddings)

ML (classification, regression, NLP, T

Full-stack API design & UI integration

Azure cloud (Azure ML, Azure OpenAI,AK

Regulated/compliance domains

SME collaboration

Agentic AI interest

Communication & stakeholder expl.

Production AI systems

Education

Bachelor's in Computer Science or equivalent

Tools

Azure ML

Azure OpenAI

AKS

FHIR/HL7 exposure

Job description

NTT DATA is seeking an Agentic AI Engineer to join our team in Los Angeles, CA. You 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 and data streams.

Responsibilities include designing agent-based workflows, building multi-agent and RAG-enabled architectures, deploying on Azure, and collaborating with SMEs to translate medical workflows into agent logic.