NTT DATA
Technology
GenAIEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“GenAI Engineer at NTT DATA. Skills: Generative AI, Machine Learning, MLOps, LLMOps. Design AI/ML solutions. Build AI/ML solutions”
What You'll Achieve.
Build scalable AI solutions; Deliver scalable AI solutions; Deploy scalable AI solutions; Scale enterprise AI capabilities; Develop secure AI systems; Develop governed AI systems; Develop high-performing AI systems
Industry & Context.
Translate business problems; Root cause analysis
What They're Looking For.
Must Have
5+ years Python, 5+ years Azure AI Foundry, 5+ years Azure OpenAI, 5+ years Azure Machine Learning, 5+ years Azure AI Search, 5+ years Cognitive Services, 5+ years LangChain, 5+ years LangGraph, 5+ years Semantic Kernel, 5+ years MCP-style agent communication patterns, 5+ years RAG pipelines, 5+ years embeddings, 5+ years vector databases, 5+ years document ingestion architectures, 5+ years CI/CD for ML, 5+ years CI/CD for LLM, 5+ years Azure DevOps pipelines, 5+ years Git-based workflows, 5+ years cloud-native deployment automation, 5+ years identity management, 5+ years access management, 5+ years secrets management, 5+ years secure deployment practices, 5+ years Responsible AI frameworks, 5+ years enterprise governance models, 5+ years Agile environments
Nice to Have
Databricks Certified Generative AI Engineer Associate, Microsoft Azure AI Engineer Associate, Azure Machine Learning Certification, Azure Data Scientist Associate, MLOps or LLMOps training, LangChain/GenAI specialization coursework
What You'll Do.
Design AI/ML solutions
Build AI/ML solutions
Deliver AI/ML solutions
Develop AI solutions using Azure
Build agent-based architectures
Design prompt engineering strategies
Optimize prompt engineering strategies
Optimize RAG pipelines
Optimize vector search
Design knowledge-grounding workflows
Optimize knowledge-grounding workflows
Build classical ML models
Train classical ML models
Evaluate classical ML models
Deploy classical ML models
Evaluate GenAI models
Implement MLOps practices
Implement LLMOps practices
Integrate AI solutions securely
Embed Responsible AI principles
Collaborate with Data Engineers
Collaborate with AI Architects
Collaborate with Security teams
Collaborate with business stakeholders
Provide engineering guidance
Mentor junior team members
Contribute to reusable components
Contribute to shared libraries
Contribute to engineering best practices
How You'll Work.
Team & Collaboration
Cross-functional teams; Agile environments; Data Engineers; AI Architects; Security teams; Business stakeholders
Process & Methodology
Agile, Scrum, Kanban
Full Job Description
Job Title: GenAI Engineer Location Preference: 100% remote in Mexico, Brasil, Peru, Chile working EST Time Zone OR onsite in Washington, D. C. Duration: 1-Year Assignment with possibility of extension NTT DATA is a team of more than 139,000 diverse professionals operating in more than 50 countries worldwide. Our sectors of activity include telecommunications, finance, industry, utilities, energy, public administration, and health. Our mission? Offer technological solutions, business, strategy, development, and application maintenance while being a benchmark in consulting. Thanks to the collaboration between teams, the human quality of our people, and the fact that we do not conform to what is established, we always seek innovation that brings us closer to the future. Our essence has led us to the forefront of technology, breaking paradigms and providing solutions that truly respond to each client's needs. Our talent has led us to be one of the top six technology companies in the world. Because #Greattech, needs #GreatPeople, like you NTT Data seeks high-achieving team players who quickly adapt to new challenges and entrepreneurial ventures. We are looking for a GenAI Engineer to work with our global client for a fully remote opportunity in LATAM working EST hours. Position Summary The GenAI Engineer is a core technical contributor responsible for designing, building, deploying, and managing AI and Machine Learning solutions across enterprise environments. This role focuses on implementing both classical ML and modern Generative AI workloads, including agent-based systems, Retrieval-Augmented Generation (RAG), and LLM-driven pipelines. The engineer ensures all AI solutions are scalable, secure, governed, and aligned with enterprise architecture and operational requirements. Key Responsibilities Design, build, and deliver end-to-end AI/ML solutions—from experimentation and prototyping to production deployment. Develop AI solutions using Azure AI Foundry, Azure OpenAI,
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