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NTT Data

Global IT services and consulting provider.

AI Engineer Advisor

AI Application EngineeringUpdated on Nov 14
Full-timeNoida, Uttar Pradesh, IndiaNo salary listed

About the Job

Requirements

  • At least 7 years of overall experience in software engineering, data engineering, or machine learning engineering.
  • At least 3 years of relevant experience in artificial intelligence or machine learning, including hands-on generative AI work.
  • Strong hands-on coding skills in Python; C# is acceptable alongside Python.
  • Hands-on experience building AI agents with at least one framework such as LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel.
  • Experience with large language models from OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI, or open-source models.
  • Strong prompt engineering skills for real business use cases.
  • Experience with retrieval-augmented generation, embeddings, and vector databases such as Pinecone, Qdrant, pgvector, or Azure AI Search.
  • Experience integrating AI with applications through REST APIs, software development kits, and tool or function calling.
  • Daily use of AI coding assistants such as Claude Code, GitHub Copilot, or Cursor.
  • Working knowledge of at least one cloud platform—Azure, AWS, or GCP—and its AI services.
  • Experience with Docker, Git, and continuous integration and continuous delivery pipelines.
  • Front-end skills to build simple agent interfaces using React, Streamlit, Gradio, or similar.
  • Experience in client-facing delivery, pre-sales, or proofs of concept.
  • A bachelor’s or master’s degree in Computer Science, Information Technology, Data Science, or a related field.
  • Ability to explain technical concepts clearly to non-technical stakeholders.

Responsibilities

  • Design, develop, and deploy AI agents and multi-agent workflows using frameworks such as LangChain, LangGraph, CrewAI, or AutoGen.
  • Connect agents to enterprise systems and data through REST APIs, software development kits, tool or function calling, and Model Context Protocol servers.
  • Write, test, and refine prompts so large language models provide accurate, consistent, and safe responses.
  • Build retrieval-augmented generation pipelines covering document ingestion, embeddings, vector databases, and retrieval tuning.
  • Use AI coding assistants such as Claude Code, GitHub Copilot, or Cursor for development, testing, code reviews, and documentation.
  • Package and deploy AI services using Docker, Kubernetes, and continuous integration and continuous delivery pipelines on Azure, AWS, or GCP.
  • Build user interfaces for human-AI interaction, including human review and approval steps.
  • Set up evaluation and monitoring for accuracy, hallucinations, latency, and cost, and act on the results.
  • Ensure solutions meet security, privacy, and responsible AI guidelines, including bias mitigation and prompt-injection safeguards.
  • Lead AI projects end to end, ensuring timely delivery and quality.
  • Mentor junior engineers, review code, and share best practices with the team.
  • Present AI opportunities and project updates to senior management and stakeholders.
  • Support requests for proposals, requests for information, solution demonstrations, and proofs of concept.
  • Document prompt strategies, agent designs, and outcomes for reuse across teams.

Desired Qualifications

  • Experience with Model Context Protocol or agent-to-agent protocols.
  • Experience with large language model evaluation and observability tools such as LangSmith, Langfuse, Ragas, or DeepEval.
  • Exposure to traditional machine learning using TensorFlow, PyTorch, or scikit-learn, and data processing with pandas, NumPy, or Spark.
  • Knowledge of knowledge graphs using Neo4j or graph-based retrieval-augmented generation.

About the Company

NTT Data

Global IT services and consulting provider.

NTT DATA is a global IT and business services provider that helps organizations run and transform their technology and operations. It delivers consulting, industry solutions, cloud migration, cybersecurity, data analytics, and managed services to modernize systems and processes. It differentiates itself through its large scale, deep sector expertise in banking, healthcare, manufacturing, public sector, and automotive, and its broad ecosystem of partners with Microsoft, SAP, AWS, and Salesforce. Its goal is to help large enterprises digitally transform and optimize operations at scale using cloud-native approaches and secure IT environments.

Company size
10,001+
Company stage
IPO
Headquarters
Tokyo, Japan
Founded
1988

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