AI Architect

Job Overview

Principal GenAI Architect – Charlotte, North Carolina, United States.

• Serve as the ultimate technical authority for GenAI architecture across the enterprise, reviewing and guiding all AI/ML use cases.
• Push the boundaries of our technical vision, acting as a forward‑thinking catalyst for how GenAI is built and deployed.
• Lead the architectural review process for all third‑party AI integrations (e.g., Service Now, Five9, Pega), ensuring they meet strict security, performance, and integration standards.
• Spearhead the growth and development of our agentic stack, designing agentic frameworks that incorporate robust workflow logic.
• Architect sophisticated retrieval systems and agent data stacks, utilizing vector databases, hybrid search, BM25, and graph‑based reasoning.
• Implement solutions for externalized long‑term memory, contextual data freshness, and Model Context Protocol (MCP) servers.
• Lead prompt and context engineering strategies to maximize model accuracy and reliability.
• Design, implement, and scale high‑performance distributed systems and AI/ML platforms.
• Optimize LLM inference, implementing advanced batching, caching strategies, and load balancing techniques.
• Evaluate and implement dynamic deployment strategies, weighing the trade‑offs of deploying small/local LLMs at the edge versus leveraging hyperscaler inferencing via cloud APIs.
• Architect and test distributed API gateways across hybrid (cloud and on‑premise) environments.
• Oversee on‑premise hardware strategy, including rigorous GPU management, utilization, and thermal/compute optimization.

• Engineering Foundation: 12–15 years of experience with strong proficiency in at least one core programming language (e.g., Python, Go, C++) and deep experience building large‑scale distributed systems.
• GenAI & LLM Expertise: 5–7 years hands‑on, practitioner‑level experience with LLM inference optimization, fine‑tuning, and deployment strategies.
• Agentic Architectures: 3–5 years experience with a proven track record of building complex agentic systems, evaluation frameworks, and advanced retrieval pipelines (RAG, Vector DBs, Graph reasoning).
• Cloud & Infrastructure: 10–12 years extensive experience with Kubernetes, Cloud Infrastructure (AWS, GCP, or Azure), and managing high‑availability platforms.
• Hardware / On‑Premise Knowledge: 8–10 years experience and understanding of GPU orchestration, resource management, and hardware optimization in on‑premise or hybrid data centers.
• Strategic Communication: 12–15 years experience and ability to navigate a matrixed organization, translate complex technical trade‑offs to leadership, and rigorously evaluate third‑party enterprise platforms.

• Domain experience in the Banking or Financial Services industry.
• Interest or hands‑on experience in integrating Blockchain technologies and decentralized frameworks.

NTT DATA is an equal‑opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.