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As an AI Engineer at NTT DATA, you will be instrumental in delivering AI solutions that drive business transformation. You will collaborate with a talented team to build and refine AI components, support end-to-end delivery, and contribute to applied innovation in Generative AI and AI Agents. This role requires a solid foundation in AI/ML engineering, strong programming skills, and exposure to cloud-based development. A degree in Computer Science or Engineering is preferred, along with at least 2 years of relevant experience. Join us to make a meaningful impact in the AI landscape.
Job Responsibility:
Build and refine AI components: You will implement key parts of ML or GenAI solutions, ensuring they follow best engineering practices
Support end-to-end delivery and productionization: You will help operationalize models and LLM applications: integrating them into cloud environments, configuring pipelines, performing quality checks, and supporting deployments
Contribute to applied innovation in GenAI and AI Agents: You will explore, prototype, and test emerging techniques in Generative AI, Large Language Models, and modular AI agent frameworks
Requirements:
Solid AI/ML Engineering Foundations: At least 2 years of experience building and deploying machine learning or Generative AI components
Strong Programming Skills (Python-focused): Comfort working with Python and common AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit‑learn, LangChain, Hugging Face, FastAPI)
Cloud-based AI Development: Exposure to cloud platforms (Azure, AWS, or GCP), CI/CD pipelines, containerization (Docker), or automated workflows
Applied Problem-Solving Mindset: Ability to translate requirements into technical tasks, run experiments, debug issues, and iterate quickly
Appreciated relevant certifications in AI/ML, cloud architecture, or MLOps
Basic knowledge of data engineering workflows
We value experience participating in client-facing activities such as demos, PoCs, workshops, or supporting technical discussions
Nice to have:
Appreciated relevant certifications in AI/ML, cloud architecture, or MLOps
Basic knowledge of data engineering workflows
We value experience participating in client-facing activities such as demos, PoCs, workshops, or supporting technical discussions