Machine Learning Engineer / AI Engineer

NTT DATA, Inc.; Charlotte (NC); On-site; USD 90,000 - 110,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

Flexible spending or health savings

AD&D insurance

Employee assistance

401k program

Additional voluntary or legally‑needed

Job summary

NTT DATA, Inc. is seeking a GenAI-focused Machine Learning Engineer to lead the CIO organization in delivering production-grade AI solutions in Charlotte, NC.

You will design, deploy, and scale GenAI capabilities using LLMs, RAG, and agentic AI patterns, while helping teams adopt enterprise AI platforms and secure, observable workflows. You will drive adoption of Azure AI and AWS Bedrock, establish guardrails, and ensure alignment with enterprise architecture, security, and governance standards.

Qualifications

• 8+ years in enterprise software or AI solution development.
• 5+ years Python with modern software practices.
• 3+ years building Generative AI/LLM apps incl. prompt engineering.
• 3+ years designing and implementing RAG with embeddings and vector search.
• 2+ years agentic AI workflows and orchestration frameworks.
• 3+ years cloud AI platforms (Azure AI/Azure OpenAI, AWS Bedrock).
• 3+ years cloud-native engineering (CI/CD, containers, observability, security).
• 2+ years in technical enablement, architecture, or engineering leadership.

Responsibilities

• Serve as GenAI engineering lead for CIO organization, translating priorities into scalable AI solutions.
• Design, develop, test, and deploy production-grade GenAI using LLMs, RAG, and agentic AI patterns.
• Accelerate high-value use cases with prototyping, reusable components, and reference architectures.
• Drive adoption of enterprise AI platforms (Azure AI, AWS Bedrock) across teams.
• Design secure RAG and agentic workflows with ingestion, embeddings, vector search, and guardrails.
• Ensure alignment with security, privacy, governance, observability, and production support standards.
• Provide workshops, reviews, and guidance on prompt engineering, RAG, orchestration, and platform usage.
• Create documentation, playbooks, and sample code as liaison between platforms and CIO teams.

Skills

GenAI engineering

Python

Prompt engineering

LLMs integration

RAG implementations

Agentic AI patterns

CI/CD & DevOps

Cloud platforms

Education

Bachelor's degree in CS/Engineering/Data Science/AI/ML

Tools

Azure AI

Azure OpenAI

AWS Bedrock

LangChain

Pinecone

FAISS

OpenSearch

pgvector

LangGraph

Job description

NTT DATA is seeking a GenAI-focused Machine Learning Engineer / AI Engineer to support an assigned CIO organization in delivering production-grade AI solutions. In this onsite role in Charlotte, North Carolina, you will design and deploy scalable GenAI capabilities using LLMs, RAG, and agentic AI patterns, while also helping teams adopt enterprise AI platforms and secure, observable workflows.

What you will do

• Serve as the primary GenAI engineering lead for a CIO organization, translating business priorities into scalable AI solutions.
• Design, develop, test, and deploy production-grade GenAI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI patterns.
• Accelerate high-value use cases through hands‑on engineering, rapid prototyping, reusable components, reference architectures, and production solutioning.
• Drive adoption of enterprise AI platforms, including Azure AI and AWS Bedrock, translating platform capabilities into practical implementation patterns.
• Design secure RAG and agentic workflows covering document ingestion, embeddings, vector search, orchestration frameworks, tools/APIs, enterprise data sources, and guardrails.
• Ensure solutions align with enterprise architecture, security, privacy, responsible AI, governance, observability, and production support standards.
• Provide technical enablement through workshops, training, design reviews, and guidance on prompt engineering, RAG, orchestration, LLM application patterns, and platform usage.
• Create reusable documentation, playbooks, quick‑start guides, sample code, and best practices, acting as a liaison between centralized AI platforms and CIO engineering teams.

Required qualifications

• 8+ years overall experience in software engineering, data engineering, machine learning engineering, or AI solution development in enterprise environments.
• 5+ years hands‑on experience delivering machine learning, AI, or data‑driven applications using Python and modern software engineering practices.
• 3+ years hands‑on experience building Generative AI / LLM applications, including prompt engineering, model integration, evaluation, and production deployment.
• 3+ years experience designing and implementing RAG solutions using embeddings, vector search/databases, document processing, retrieval techniques, and grounding patterns.
• 2+ years experience developing agentic AI or multi‑step AI workflows using orchestration frameworks, tool/function calling, APIs and enterprise integrations.
• 3+ years experience with cloud AI/ML platforms, including Azure AI / Azure OpenAI, AWS Bedrock, etc .
• 3+ years experience with cloud-native engineering, including CI/CD, containers, observability, security controls, and production deployment practices.
• 2+ years experience in technical enablement, architecture, consulting, or engineering leadership, including workshops, mentoring, reusable guidance, and application of responsible AI/governance requirements.

Technologies

• Python, LLMs, RAG, agentic AI patterns
• Azure AI, AWS Bedrock, Azure OpenAI
• CI/CD, containers, observability
• Embeddings, vector search, vector search/databases, document ingestion
• Orchestration frameworks, tools/APIs, enterprise data sources, guardrails
• Prompt engineering, model integration, evaluation
• Enterprise architecture, security, privacy, responsible AI, governance
• Azure AI Search, OpenSearch, Pinecone, pgvector, FAISS
• LangChain, LangGraph, Semantic Kernel, LlamaIndex, AutoGen
• LLMOps / MLOps, red-teaming

Education

Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, Machine Learning, or equivalent.

Benefits

• Medical, dental, and vision insurance
• Flexible spending or health savings account
• AD&D insurance
• Employee assistance
• Participation in a 401k program
• Additional voluntary or legally-required benefits

Nice to have

• Experience with LangChain, LangGraph, Semantic Kernel, LlamaIndex, AutoGen, or comparable LLM/agent orchestration frameworks.
• Experience with vector technologies such as Azure AI Search, OpenSearch, Pinecone, pgvector, FAISS, or equivalent platforms.
• Experience with LLMOps / MLOps, prompt and model evaluation, AI observability, guardrails, red-teaming, and production quality measurement.
• Experience building reusable GenAI accelerators/reference architectures or delivering AI solutions in highly regulated enterprise environments such as financial services.

Travel: Travel as required based on business and CIO-aligned engagement needs.

Compensation: The starting pay range for this role is $65.67 to $80.11 per hour.