NTT DATA is seeking innovative and passionate AI Engineers to join our dynamic team in Bangalore, India. This role focuses on the design, development, and integration of cutting-edge AI and Generative AI applications. You will leverage Large Language Models (LLMs) and modern AI frameworks to build intelligent systems capable of complex reasoning and interaction.

As an AI Engineer, you'll contribute to building robust AI agents, integrating them with enterprise systems, and optimizing their performance. The position involves developing advanced prompt engineering techniques, implementing Retrieval-Augmented Generation (RAG) solutions, and creating reusable AI components and APIs. Your work will directly impact how AI capabilities are embedded into web applications, enterprise platforms, and business processes.

This role offers an opportunity to work with a leading global technology services company, driving digital transformation and responsible innovation. We are committed to fostering an inclusive and adaptable work environment where you can grow your career.

Key responsibilities include designing and developing AI and Generative AI applications using LLMs, building and integrating AI agents, and developing prompt engineering capabilities. You will implement RAG solutions with enterprise data, create reusable AI components and APIs, and integrate AI into various platforms and business systems.

Further duties involve integrating commercial and open-source LLMs, developing single and multi-agent workflows, and implementing agent tools, memory, and state management. Optimizing prompts, model parameters, and retrieval strategies for quality and efficiency is crucial. You will also develop AI guardrails, input/output validation, and error-handling mechanisms.

Responsibilities extend to building ingestion and indexing pipelines for enterprise content, developing semantic and hybrid search capabilities, and integrating vector databases. Testing AI applications, building evaluation datasets, and performing root-cause analysis for AI issues are also integral parts of the role. You will support the deployment of AI applications and services, implement CI/CD pipelines, and manage AI observability and LLMOps/MLOps processes.

To be successful in this role, strong programming skills in Python and experience developing production-grade applications are essential. Hands-on experience with Generative AI, LLMs, RAG, and Agentic AI is required. You should have experience integrating LLM platforms like OpenAI, Azure OpenAI, Anthropic, Google Gemini, or AWS Bedrock.

Familiarity with AI frameworks such as LangChain, LangGraph, Semantic Kernel, or AutoGen is necessary. Experience with embeddings, semantic search, and vector databases (e.g., Azure AI Search, Pinecone, Elasticsearch) is also a key requirement. A strong understanding of REST APIs, JSON, microservices, enterprise integration patterns, and experience with SQL/NoSQL databases are expected.

Proficiency in Git and modern software development practices is required. Knowledge of Docker, Kubernetes, CI/CD, DevOps, and cloud-native development is important. Experience working with Azure, AWS, or Google Cloud Platform, along with an understanding of authentication, authorization, API security, and secrets management, is also necessary.