AI Architect

NTT DATA''s Client is currently seeking an AI Architect to join their team in Ft. Worth, Texas (US-TX), United States (US). (DFW area)

Seeking an experienced AI Architect to design and lead enterprise-scale AI, ML, and Generative AI solutions built on AWS and Azure as the core AI foundation, with Microsoft Copilot as the primary user experience layer. The role is responsible for designing the end-to-end AI solution architecture, ensuring alignment with enterprise systems, scalability, and governance standards while integrating AI into the broader IT landscape. It requires deep expertise in RAG (Retrieval-Augmented Generation) and Agentic AI architecture on cloud-native platforms, enabling intelligent, scalable, and production-ready AI systems after understanding the current product architecture. The candidate should also be able to conduct POCs to demonstrate proof of design considerations.

Platform & Enablement Roles
AI Platform Admin (M365, copilot Studio) Manages AI platforms and environments, including access provisioning, governance controls, and policy enforcement (e.g., DLP, security, and compliance).
AI Reusable Utility Develops reusable components (e.g., prompts, connectors, APIs, templates) to accelerate AI solution delivery and promote standardization across use cases.
AI Common Infrastructure, Framework & Observability Architect (AWS and Azure) Designs and maintains the foundational AI infrastructure, frameworks, and observability capabilities (telemetry, monitoring, metrics) required for scalable, reliable, and governed AI operations.

Core Responsibilities
Architectural Design: Define the end-to-end blueprints spanning data ingestion, model training, inference, and continuous monitoring. design end-to-end artificial intelligence solutions ensuring models scale efficiently align with enterprise systems and meet governance standards. They act as the vital bridge linking theoretical AI models built by data scientists with production-ready, secure applications integrated into the broader IT landscape.
Enterprise Integration: Seamlessly embed AI/ML features and multi-agent workflows into legacy applications, ERPs, and cloud-native systems.
Governance & Compliance: Implement ethical AI guardrails, model risk management, data privacy protections and explainability standards.
Scalability & MLOps: Establish CI/CD for AI, model versioning, automated retraining, and drift detection to prevent performance degradation.
Tech Stack Strategy: Make crucial "build vs. buy " decisions for infrastructure, weighing tradeoffs of on-premises, hybrid, and cloud environments.
Leadership & Collaboration:
Serve as a technical thought leader for AI, GenAI, and data platforms.
Mentor data scientists, ML engineers, and data engineers.
Collaborate with business and product teams to translate requirements into AI-driven solutions.
Evaluate emerging AI technologies and guide strategic adoption.
AI, ML & GenAI Architecture
Design and define end-to-end AI solution architectures covering data ingestion, model training, deployment, monitoring, and governance, ensuring alignment with enterprise systems and IT landscape while meeting scalability and governance standards.
Design scalable, cloud-native AI platforms on AWS and Azure.
Architect solutions for both batch and real-time inference workloads.
RAG (Retrieval-Augmented Generation)
Architect and implement RAG pipelines using structured and unstructured enterprise data.
Design ingestion, chunking, embedding, and retrieval strategies for RAG systems.
Integrate vector databases (e.g., Pinecone, FAISS, Milvus, Azure AI Search, Amazon OpenSearch).
Ensure relevance, freshness, observability, and security of RAG-based AI systems.
Agentic AI & Autonomous Systems

Design Agentic AI architecture enabling autonomous decision-making and task execution.
Orchestrate multi-agent systems using tools, memory, and reasoning workflows.
Implement guardrails, human-in-the-loop controls, and observability for agent-based systems.
Enable enterprise use cases such as AI assistants, Microsoft Copilot-integrated workflows, task automation, and decision intelligence.
MLOps & LLMOps

Define and implement MLOps / LLMOps frameworks for CI/CD, versioning, monitoring, and drift detection.
Enable experimentation, evaluation, and governance of ML models and LLM-based systems.
Ensure compliance with security, privacy, and responsible AI guidelines.
Cloud & Platform Engineering

Architect AI solutions on AWS and Azure as the primary cloud platforms, integrating Microsoft Copilot as the enterprise user experience layer.
Integrate AI platforms with enterprise applications, APIs, and data sources.
Design highly available, secure, and scalable AI systems.
Required Skills
Engineering Foundation: 7+ years of deep knowledge of MLOps, containerization (Docker/Kubernetes), and CI/CD pipelines.
Cloud Platforms: 5+ years of advanced expertise in deploying on major hyperscalers like AWS Machine Learning, Azure AI, or Google Vertex AI.
Data Management: 5+ years of Proficiency in designing feature stores, vector databases, and real-time/batch data pipelines.
AI/ML Frameworks: 3 to 5 years of familiarity with concepts like Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), and frameworks like PyTorch or TensorFlow.

#LI-NorthAmerica

About NTT DATA:

NTT DATA is a $30 billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us at us.nttdata.com

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Where required by law, NTT DATA provides a reasonable range of compensation for specific roles. The starting hourly range for this remote role is ($80 - 90/hourly ). This range reflects the minimum and maximum target compensation for the position across all US locations. Actual compensation will depend on several factors, including the candidate''s actual work location, relevant experience, technical skills, and other qualifications.

This position is eligible for company benefits that will depend on the nature of the role offered. Company benefits may include medical, dental, and vision insurance, flexible spending or health savings account, life, and AD&D insurance, short-and long-term disability coverage, paid time off, employee assistance, participation in a 401k program with company match, and additional voluntary or legally required benefits.