AI Specialist / GenAI Architect

The AI Specialist / GenAI Architect is a senior technical role responsible for designing end-to-end AI solution architectures and ensuring that AI systems are secure, scalable, enterprise‑aligned, and production‑ready. This role bridges advanced solution architecture with operational execution—ensuring AI systems are effectively designed, deployed, monitored, and maintained throughout their lifecycle.
The individual will serve as a technical authority across AI architecture, integration, deployment, governance, and operational stability.

• →Design end-to-end AI solution architectures across
• →Track A: Low-code / Copilot-based AI
• →Track B: Code-centric and custom AI
• →Track C: Platform-embedded AI
• →Select appropriate AI approaches, tools, platforms, and architectural patterns based on enterprise standards and use-case requirements.
• →Define integration patterns between AI components, enterprise systems, data platforms, APIs, and shared services.
• →Ensure AI solutions align with enterprise architecture frameworks, cloud standards, security principles, and long‑term technology roadmaps.
• →Contribute to AI reference architectures, reusable patterns, best practices, and technical standards.
• →Deploy AI solutions into production following enterprise processes for release management, change control, and solution hardening.
• →Conduct architectural reviews, production readiness assessments, and validation checkpoints for new AI workloads.
• →Implement CI/CD pipelines, MLOps practices, and automated deployment frameworks for AI and data-driven solutions.
• →Operate and monitor AI systems in production, ensuring availability, performance, reliability, and cost optimization.
• →Implement robust monitoring, logging, alerting, and observability capabilities for AI models, pipelines, and integrations.
• →Support scalability planning for AI workloads including capacity forecasting and cost modeling.
• →Detect, analyze, and resolve production incidents impacting AI models, data pipelines, or integrations.
• →Perform root-cause analysis and contribute to incident response processes related to AI workloads.
• →Ensure compliance with AI governance principles, Responsible AI requirements, risk management, and security controls.
• →Collaborate with cross-functional teams including AI Engineering, Data Engineering, Security, Cloud Architecture, and IT Operations.
• →Serve as an escalation point for complex, cross-domain AI technical challenges.

• Strong ability to design full AI architectures from ingestion to deployment and ongoing operations.
• Deep understanding of:
• Generative AI
• Predictive and analytical models
• RAG (Retrieval-Augmented Generation) architectures
• Agent-based systems
• Ability to weigh architectural trade-offs related to scalability, performance, reliability, security, and cost.
• Experience deploying AI solutions in enterprise production environments.
• Demonstrated ability to manage operational dependencies across infrastructure, data platforms, applications, and security tools.

• Experience aligning AI solutions with enterprise architecture and cloud governance frameworks.
• Knowledge of integration patterns, microservices, APIs, and event-driven architectures.
• Familiarity with shared services, cloud-native design, and distributed systems.

• Experience implementing CI/CD for AI and data workloads.
• Ability to establish monitoring, logging, and observability pipelines.
• Strong background in reliability engineering, operational resilience, and continuous improvement.

• Awareness of how governance, privacy, and Responsible AI principles impact architecture and operations.
• Ability to incorporate security standards, controls, and compliance requirements into solution design.

• Azure AI Engineer Associate
• Azure Solutions Architect Expert
• DevOps and/or MLOps training
• RAG & vector database design and implementation training
• Kubernetes or cloud-native architecture fundamentals
• Privacy-by-design or data protection training

This role directly supports the successful deployment and operation of scalable, secure, enterprise-grade AI systems. The individual ensures AI solutions are not only technically sound but also reliable, governed, and aligned with best practices across architecture, security, and cloud strategy.

• Ability to operate as a senior technical authority in AI architecture
• Opportunity to shape enterprise AI architecture, standards, and operational frameworks
• Work at the intersection of solution architecture, AI engineering, MLOps, and operational excellence

Empowerment and rewards are the cornerstone of our career development model. We are a young, fast-growing company, with a highly innovative and entrepreneurial spirit, because of this professional experience and growth will be unmatched. Our talent and positive attitude allow us to transform our goals into achievements, and projects into realities.

NTT Data is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. NTT Data is an Equal Opportunity Employer Male/Female/Disabled/Veteran and a VEVRAA Federal Contractor.