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Machine Learning Engineer / AI Engineer

NTT DATA Charlotte, NC

Charlotte, NC

Today

$65 - $80/hr Full time Agentic Ai Ai Agent Ai Platform

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Job Description

NTT DATA is hiring a GenAI-focused Machine Learning Engineer / AI Engineer to support a CIO organization in designing, developing, and deploying production-grade AI solutions. This onsite role in Charlotte, North Carolina centers on building with LLMs, Retrieval-Augmented Generation (RAG), and agentic AI patterns, alongside secure, observed workflows and technical enablement for enterprise teams.

Role summary

You will serve as a primary GenAI engineering lead, translating business priorities into scalable solutions. The work includes enterprise AI platform adoption, solutioning production deployments, and supporting adoption through training, workshops, design reviews, and reusable engineering assets.

Responsibilities

Partner with an assigned CIO organization as the primary GenAI engineering lead and translate business priorities into scalable AI solutions.
Design, develop, test, and deploy production-grade GenAI solutions using LLMs, 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 such as Azure AI and AWS Bedrock, translating platform capabilities into practical implementation patterns.
Design secure RAG and agentic workflows involving 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.
Deliver workshops, training, design reviews, and technical guidance covering prompt engineering, RAG, orchestration, LLM application patterns, and platform usage.
Develop reusable documentation, playbooks, quick-start guides, sample code, and best practices, while acting as a liaison between centralized AI platform and CIO engineering teams.

Required qualifications

Minimum 8 years overall software engineering, data engineering, machine learning engineering, or AI solution development experience in enterprise environments.
Minimum 5 years hands-on experience designing and delivering machine learning, AI, or data-driven applications using Python and modern software engineering practices.
Minimum 3 years hands-on experience building Generative AI / LLM applications, including prompt engineering, model integration, evaluation, and production deployment.
Minimum 3 years experience designing and implementing RAG solutions using embeddings, vector search/databases, document processing, retrieval techniques, and grounding patterns.
Minimum 2 years experience developing agentic AI or multi-step AI workflows using orchestration frameworks, tool/function calling, APIs, and enterprise integrations.
Minimum 3 years experience with cloud AI/ML platforms, including Azure AI / Azure OpenAI, AWS Bedrock, or comparable enterprise AI services.
Minimum 3 years experience with cloud-native engineering, CI/CD, containers, observability, security controls, and production deployment practices.
Minimum 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, Large Language Models (LLMs)
Retrieval-Augmented Generation (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

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 (USD per hour).

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