NTT DATA is seeking a skilled AWS AI Engineer to develop and deploy advanced AI solutions on the AWS cloud. This role focuses on leveraging Generative AI, Large Language Models (LLMs), and intelligent automation to build scalable, enterprise-grade applications. You will collaborate with cross-functional teams to deliver innovative AI-powered business solutions, requiring a blend of software engineering excellence and deep expertise in AI/ML services.

This is an exciting opportunity to join a forward-thinking organization and contribute to cutting-edge AI initiatives. We are committed to fostering an inclusive and adaptable work environment where individuals can grow and innovate.

Design, develop, and deploy enterprise AI applications utilizing AWS services and modern AI frameworks. Build solutions involving Generative AI, Conversational AI, AI Assistants, and Agentic AI. Translate complex business needs into secure, scalable, and resilient AI applications. Create reusable AI frameworks, APIs, and integration services. Develop AI agents and orchestrate multi-agent workflows. Implement prompt engineering, context management, and evaluation frameworks. Evaluate and integrate various open-source and commercial models. Design and develop AI solutions using Amazon Bedrock, SageMaker, Amazon Q, and related AWS services. Integrate AI capabilities into business applications to enhance efficiency and productivity.

Optimize AI solutions for performance, latency, and cost. Implement MLOps and LLMOps for model deployment and governance. Support production operations, troubleshooting, and ensure compliance with security and Responsible AI standards. Collaborate with architects, data scientists, and stakeholders, while mentoring junior engineers.

A Bachelor's degree in Computer Science, Engineering, Data Science, or a related field is required, along with a minimum of 5 years in software engineering or application development. At least 2 years of hands-on experience developing AI, Machine Learning, or Generative AI solutions is essential. Proficiency in Python and modern software engineering practices, along with experience building cloud-native applications on AWS, is crucial. Strong understanding of API development, microservices, distributed systems, and cloud architectures is expected. Experience integrating LLMs and Generative AI into enterprise applications, and deploying AI workloads in production, is necessary. Excellent communication, stakeholder management, and problem-solving skills are key.

A Master's degree in a relevant field, AWS certifications, and experience with Amazon Bedrock and Amazon Q are preferred. Experience with MLOps, LLMOps, Docker, and Kubernetes is also beneficial.