AI Architect
US$102,500 – US$166,000 / yr base salary
Posted 5 Oct 2026
Advertised as “AI Architect - Hybrid in Charlotte, NC”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 10+ yrs
- Management level
- People management
- Employment
- Hybrid
| Base salary | US$102,500 – US$166,000 / yr |
|---|
Field of studyArtificial Intelligence, Computer Science, Data Science, Engineering (or related)
Study levelBachelor's
Req ID: 393086
NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.
We are currently seeking a AI Architect - Hybrid in Charlotte, NC to join our team in Charlotte, North Carolina (US-NC), United States (US).
AI Architect
Experience: 10+ years in technology / software architecture | 5+ years AI/ML | 3+ years Generative AI
Focus: Generative AI | LLMs | RAG | AI Agents | Cloud AI | Enterprise Architecture
Industry: Financial Services / Regulated Industries preferred
About the Role
We are seeking an experienced AI Architect to design and lead the development of enterprise-scale Artificial Intelligence and Generative AI solutions.
This role will define AI architecture, technology strategy, and implementation patterns while helping organizations move AI initiatives from proof of concept to secure, scalable production solutions.
The ideal candidate combines strong enterprise architecture experience with hands-on knowledge of LLMs, Generative AI, RAG, AI agents, cloud platforms, AI/ML services, and enterprise integration. You will work closely with business leaders, data scientists, ML engineers, software developers, security teams, and enterprise architects to turn emerging AI capabilities into practical business solutions.
Responsibilities:
AI & Enterprise Architecture
- Design and lead AI and Generative AI architectures for enterprise applications and business solutions.
- Define AI technology strategies, reference architectures, standards, and implementation roadmaps.
- Translate business requirements into secure, scalable, and production-ready AI solutions.
- Evaluate and recommend AI models, platforms, frameworks, and cloud services based on business and technical requirements.
- Establish architecture patterns that support scalability, reliability, performance, security, and cost efficiency.
- Guide AI initiatives from initial concept and PoC through production implementation.
Generative AI & LLM Solutions
-
Design solutions leveraging LLMs, Generative AI, RAG, prompt engineering, AI agents, and AI/ML services.