AI Engineer (Bangalore or Remote, KA, IN)

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 Engineer to join our team in Bangalore or Remote, Karnātaka (IN-KA), India (IN). Job Summary Looking for AI engineer to Build, integrate, and operationalize AI/ML models and agent workflows; collaborate with architects and data teams to deploy scalable, production-grade AI solutions. He should have extensive experience building, deploying, and operating enterprise grade AI and machine learning solutions in production. They bring deep expertise in generative AI, large language models, NLP, and multimodal systems, along with strong proficiency in Python or similar languages and modern ML frameworks such as PyTorch or TensorFlow. This individual has a proven ability to architect and operationalize AI solutions in cloud environments like AWS, Azure, or GCP using modern MLOps, CI/CD, containerization, and monitoring practices. They think holistically about AI systems, ensuring seamless integration with enterprise platforms while maintaining high standards for security, governance, and quality. Strong communication skills, cross functional collaboration, and a passion for mentoring other engineers are essential, with experience in regulated environments such as healthcare strongly preferred. 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

Advanced Solution Development • Build, deploy, and optimize LLM based, multimodal, and predictive AI models. • Develop intelligent automation to streamline workflows and reduce operational friction. • Implement NLP, conversational AI, and real time generative systems across modalities. AI System Integration & Full Stack Engineering • Oversee AI system integration with enterprise platforms, cloud services, APIs, and data pipelines. • Architect and maintain production grade ML infrastructure, including CI/CD and monitoring. • Operationalize AI/ML models in cloud environments such as AWS, Azure, or GCP. Governance, Quality & Compliance • Ensure AI solutions meet regulatory and internal governance