GenAI Engineer

GenAI Engineer - Fully Remote (LATAM EST)

NTT DATA is a global leader in digital transformation, comprised of over 139,000 diverse professionals across more than 50 countries. We are committed to innovation and delivering technological solutions that address complex client needs, establishing ourselves as a benchmark in consulting. Our mission is to bring the future closer through collaboration and a relentless pursuit of innovation. We believe that #Greattech needs #GreatPeople, and we are looking for talented individuals like you to join our team.

NTT Data is looking for high-achieving, adaptable team players to join our global client initiative as a GenAI Engineer. This is a fully remote opportunity for candidates in Mexico, Brazil, Peru, or Chile, requiring work within the EST Time Zone. The assignment is for one year with the possibility of extension.

Position Summary

The GenAI Engineer will be a core technical contributor responsible for the entire lifecycle of AI and Machine Learning solutions, from design and development to deployment and management within enterprise environments. This role emphasizes implementing both classical ML and modern Generative AI workloads, including agent-based systems, Retrieval-Augmented Generation (RAG), and LLM-driven pipelines, ensuring all solutions are scalable, secure, governed, and aligned with enterprise architecture.

Key Responsibilities

• Design, build, and deliver end-to-end AI/ML solutions, from experimentation and prototyping to production deployment.
• Develop AI solutions utilizing Azure AI Foundry, Azure OpenAI, Azure Machine Learning, and related Azure AI services.
• Construct agent-based architectures employing frameworks such as LangChain, LangGraph, Semantic Kernel, and MCP-style orchestration patterns.
• Design and optimize prompt engineering strategies, RAG pipelines, embeddings, vector search, and knowledge-grounding workflows.
• Build, train, evaluate, and deploy classical ML and GenAI models using Azure Machine Learning, including pipelines, feature engineering, model registry, and experiment tracking.
• Implement MLOps and LLMOps practices, encompassing CI/CD, automated testing, responsible deployment, model monitoring, drift detection, and performance optimization.
• Securely integrate AI solutions with enterprise systems, APIs, and event-driven architectures.
• Embed Responsible AI principles—fairness, explainability, transparency, and human-in-the-loop controls—into solution design and development.
• Collaborate closely with Data Engineers, AI Architects, Security teams, and business stakeholders to deliver scalable, compliant AI solutions.
• Provide engineering guidance, mentor junior team members, and contribute to reusable components, shared libraries, and engineering best practices.

Requirements

#### Technical Skills & Platforms

• Strong hands-on experience building and deploying AI solutions on Azure, including Azure AI Foundry, Azure OpenAI, Azure Machine Learning, Azure AI Search, and Cognitive Services.
• Solid understanding of machine learning concepts, including feature engineering, model training, evaluation, hyperparameter tuning, and operational deployment.
• Experience deploying both predictive ML and GenAI solutions in enterprise settings.

#### Generative AI & Agent Systems

• Hands-on experience with LLM-based system development, agent orchestration, and tool automation using frameworks such as:
• LangChain
• LangGraph
• Semantic Kernel
• MCP-style agent communication patterns
• Experience implementing RAG pipelines, embeddings, vector databases, and document ingestion architectures.
• Strong understanding of LLM constraints, prompt optimization, hallucination mitigation, and output validation strategies.

#### MLOps, LLMOps & DevOps

• Experience implementing CI/CD for ML and LLM workloads, including testing, monitoring, versioning, and automated deployment.
• Familiarity with Azure DevOps pipelines, Git-based workflows, and cloud-native deployment automation.
• Ability to balance rapid prototyping with strong engineering rigor, reliability practices, and production-readiness.

#### Cloud, Security & Governance

• Understanding of cloud-native patterns, containerization, and scalable AI infrastructure.
• Knowledge of identity, access management, secrets management, and secure deployment practices for AI systems.
• Familiarity with Responsible AI frameworks and enterprise governance models.

#### Collaboration & Delivery

• Ability to translate business problems into practical, scalable AI solutions.
• Strong communication and cross-functional collaboration skills.
• Experience working within Agile environments (Scrum, Kanban) delivering iteratively and incrementally.

#### Preferred Certifications & Training

• Databricks Certified Generative AI Engineer Associate
• Microsoft Azure AI Engineer Associate
• Azure Machine Learning Certification
• Azure Data Scientist Associate (optional)
• MLOps or LLMOps training
• LangChain/GenAI specialization coursework

Role Impact

This role is central to building and scaling enterprise-ready AI capabilities, enabling the development of secure, governed, high-performing AI systems that support organizational innovation, automation, and decision intelligence.

Why This Opportunity Is Attractive

• Work with cutting-edge AI technologies and modern GenAI frameworks.
• Lead hands-on development of AI systems deployed at enterprise scale.
• Collaborate with cross-functional experts across architecture, engineering, and security.

Why NTT Data?

Empowerment and rewards are the cornerstone of our career development model. As a young, fast-growing company with a highly innovative and entrepreneurial spirit, your professional experience and growth will be unmatched. Our talent and positive attitude allow us to transform goals into achievements and projects into realities.

NTT Data is committed to hiring and retaining a diverse workforce and is proud to be an Equal Opportunity/Affirmative Action-Employer.