Overview

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.

Responsibilities

• Define and design end-to-end AI/ML architectures, including data pipelines, model lifecycle, and deployment frameworks.
• Establish best practices, standards, and reusable frameworks for ML and Generative AI solutions.
• Provide architectural guidance on model selection, optimization strategies, and scalability considerations.
• Ensure systems are designed for high availability, performance, and cost efficiency.
• Design and oversee development of LLM-based enterprise solutions (chatbots, summarization systems, semantic search, copilots).
• Define prompt engineering strategies, RAG architectures, and orchestration frameworks (e.g., LangChain, LlamaIndex).
• Evaluate and select LLM providers, open-source models, and fine-tuning approaches.
• Architect secure and scalable integrations with APIs (OpenAI, Azure OpenAI, etc.).
• Lead design of vector database strategies and embedding pipelines.
• Architect enterprise MLOps frameworks, including CI/CD pipelines, model governance, and monitoring systems.
• Define model lifecycle management standards (MLflow, Langfuse, etc.).
• Oversee deployment strategies across cloud platforms (Azure preferred), including Databricks integration.
• Drive adoption of containerization (Docker), orchestration (Kubernetes), and Infrastructure as Code (Terraform).
• Establish AI governance frameworks, ensuring compliance with GDPR, HIPAA, and enterprise security standards.
• Define policies for responsible AI, model explainability, and risk mitigation.
• Ensure data privacy, security, and auditability across all AI systems.
• Act as a technical leader and mentor for AI/ML engineers and data scientists.
• Collaborate with business stakeholders, product owners, and engineering teams to align AI initiatives with business goals.
• Drive architecture reviews, design decisions, and technical roadmaps.
• Communicate complex architectural concepts to both technical and executive stakeholders.

Qualifications

• Strong expertise in machine learning, deep learning, and NLP architectures.
• Proven experience designing large-scale AI/ML systems and platforms.
• Advanced proficiency in Python and ML frameworks (PyTorch, TensorFlow, etc.).
• Deep experience with LLMs (GPT, BERT, open-source models) and Transformer architectures.
• Expertise in RAG, prompt engineering, fine-tuning, and LLM evaluation frameworks.
• Experience designing enterprise-grade GenAI applications.
• Strong experience with Azure AI/ML ecosystem, Databricks, and cloud-native architectures.
• Expertise in CI/CD, model deployment, monitoring, and observability.
• Familiarity with containerization, Kubernetes, and distributed systems.
• Proven ability to design scalable, modular, and secure systems.
• Strong understanding of microservices, APIs, and event-driven architectures.
• Experience leading technical teams and driving architecture decisions.
• Strong problem-solving, decision-making, and stakeholder management skills.

Nice to have

• Experience in healthcare or regulated industries (HIPAA, GDPR).
• Familiarity with vector databases (Pinecone, FAISS, Milvus).
• Exposure to Responsible AI frameworks and AI governance models.
• Certifications in Azure AI, AWS ML, or Enterprise Architecture frameworks.

Education

• Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
• Relevant certifications in Cloud, AI/ML, or Architecture are a plus.
• Strong communication skills with ability to influence cross-functional teams and leadership.
• Strategic thinker with a forward-looking approach to AI innovation.
• Ability to operate in global, distributed environments.