Join NTT DATA as an AI Engineer Advisor, specializing in Agentic AI. This role focuses on designing, building, and deploying advanced AI agents and Generative AI solutions for enterprise applications.

You will develop agents capable of complex task planning, tool utilization, and multi-step workflows. The position requires a deep understanding of prompt engineering, Retrieval-Augmented Generation (RAG) pipelines, and seamless integration with existing systems. Daily use of AI coding assistants is integral to this role, enhancing development speed and efficiency.

This is an opportunity to collaborate with cross-functional teams, including data scientists, software engineers, and product owners, to drive AI solutions from conception to production. If you are passionate about innovation and ready to grow with a forward-thinking organization, we encourage you to apply.

Key responsibilities include designing and deploying AI agents and multi-agent workflows using frameworks like LangChain, LangGraph, CrewAI, or AutoGen. You will integrate these agents with enterprise systems via REST APIs, SDKs, and tool/function calling.

Crafting precise prompts for LLMs to ensure accurate and safe outputs, and building robust RAG pipelines are crucial. This involves managing document ingestion, embeddings, and vector databases. You'll leverage AI coding assistants for development, testing, and code reviews.

Deployment will utilize Docker, Kubernetes, and CI/CD pipelines on major cloud platforms. Building user interfaces for human-AI interaction, including review steps, is also part of the role. Ensuring solutions meet security, privacy, and responsible AI guidelines is paramount. Furthermore, you will lead AI projects, mentor junior engineers, and present project updates to stakeholders.

We are seeking candidates with a strong foundation in software engineering, data engineering, or ML engineering, including at least 7 years of overall experience and 3+ years dedicated to AI/GenAI.

Essential skills include hands-on proficiency in Python, experience with AI agent frameworks (LangChain, LangGraph, CrewAI, AutoGen), and familiarity with major LLMs (OpenAI, Anthropic, Google, Azure). Strong prompt engineering skills and experience with RAG, embeddings, and vector databases are required.

Candidates must demonstrate experience integrating AI with applications through APIs and SDKs, daily use of AI coding assistants, and working knowledge of at least one cloud platform (Azure, AWS, GCP). Proficiency with Docker, Git, CI/CD pipelines, and excellent problem-solving and communication skills are also necessary. Experience in client-facing roles or pre-sales is a significant advantage.