GenAI RAG Architect / Engineer — Enterprise AI Infra Lead

NTT DATA, Inc.; Dallas (TX); On-site; USD 140,000 - 200,000; Full time

Job summary

NTT DATA, Inc. in Dallas, TX seeks a RAG Architect/Engineer to lead enterprise GenAI solutions. You will design and implement vector databases, infrastructure, and scalable retrieval systems to support LLMs and AI agents.

Collaborate with product, data science, and software teams to deliver robust GenAI architectures. Role involves hands-on development, architectural leadership, and ensuring ethical AI practices while evaluating new GenAI models and tools to advance the organization’s AI

Qualifications

• 5+ years building enterprise AI applications with LLMs.
• 3+ years using pre-trained language models via APIs/frameworks.
• 3+ years using NLP libraries (NLTK, SpaCy, Gensim, BERT, SBERT).
• 5+ years Python in enterprise environments.

Responsibilities

• Design and optimize vector databases to support LLM models across GenAI tools.
• Architect, develop, and scale GenAI infrastructure for data storage, processing and retrieval.
• Lead architecture decisions with external GenAI providers to ensure scalable and cost-effective solutions.
• Collaborate with product owners and engineers to translate business needs into GenAI solutions.
• Drive model optimization and fine-tuning for large language models to improve performance.
• Present architectural designs to non-technical stakeholders; translate AI concepts into business insights.

Skills

LLMs & NLP understanding

RAG architectures

AI Agents

Python

GenAI infrastructure

LangChain / LangGraph / EmbedChain

Cloud platforms (Azure/AWS)

Education

Bachelor’s degree in Computer Science or Data Science

Tools

Hugging Face

LangChain

LangGraph

EmbedChain

Azure

AWS

Job description

NTT DATA, Inc. in Dallas, TX seeks a RAG Architect/Engineer to lead enterprise GenAI solutions. You will design and implement vector databases, infrastructure, and scalable retrieval systems to support LLMs and AI agents.

Collaborate with product, data science, and software teams to deliver robust GenAI architectures. Role involves hands-on development, architectural leadership, and ensuring ethical AI practices while evaluating new GenAI models and tools to advance the organization’s AI