AI Architect

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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.

We are currently seeking a AI Architect to join our team in Charlotte, North Carolina (US-NC), United States (US).

As an AI Architect at Lead Consultant level, you will lead AI projects from conception through deployment for clients across industries, translating business challenges into working AI solutions. You will design and build the major components of those solutions, and act as the technical lead for the work streams you own within a client engagement.

The role spans the AI lifecycle — from discovery and solution design through proof of concept, production implementation, and operational improvement. The scope includes machine learning, predictive analytics, natural language processing, computer vision, intelligent automation, and Generative AI.

This is a hands-on architecture role. Expect roughly 70% of your time hands-on — building reference implementations, prototypes, production services, and integration work — and roughly 30% on design, technical leadership, and mentoring. Engagement models vary, and some client contexts require sustained hands-on delivery alongside the engineering team.

• Lead assigned AI projects from conception through deployment, owning design and delivery for the work streams you are accountable for.
• Translate business challenges into AI solution designs, and evaluate the business impact and expected return of the approaches you propose.
• Design and implement major components of enterprise AI solutions across applications, integration, data, AI/ML, and infrastructure.
• Design and build AI solution patterns across ML and GenAI — LLM applications, retrieval-augmented generation, agents, orchestration, embeddings, vector and graph-based retrieval, model integrations, and evaluation.
• Conduct data preprocessing, feature engineering, and dataset preparation for AI workloads.
• Build prototypes, proofs of concept, reference implementations, and production-ready AI services.
• Optimize AI models and inference workloads for performance, scalability, and cost, including on distributed computing frameworks and AI-optimized hardware.
• Design data storage and retrieval approaches for AI workloads across databases, data lakes, and vector or graph stores.
• Apply secure-by-design practices — authentication, RBAC, secrets management, encryption, private networking, data protection, auditability, and authorization-aware data retrieval.
• Implement responsible-AI controls, including content safety, PII protection, bias identification and mitigation, prompt-injection defenses, and human review.
• Work within client data governance requirements and applicable data privacy regulation in everything you design and deliver.
• Apply MLOps, LLMOps, and GenAIOps practices — CI/CD, version control, model and prompt versioning, infrastructure as code, testing, evaluation, monitoring, tracing, and lifecycle management.
• Communicate AI concepts, design decisions, and trade-offs clearly to client technical, product, and business teams, and collaborate across delivery, data, infrastructure, and security functions to integrate AI solutions.
• Mentor engineers and junior team members in AI engineering and architecture practices.
• Contribute to reusable patterns, accelerators, and delivery playbooks; stay current with emerging AI technologies; and provide technical input to discovery workshops, solution shaping, and effort estimates.

The experience periods below overlap and are not…