Client-Facing AI & Data Engineer (Hybrid)

NTT America, Inc.; Diegem; Ibrido; EUR 90.000 - 120.000; Tempo pieno

Vantaggi offerti da questo lavoro

Annual bonus

Lunch vouchers

Company car or Mobility budget

Private health insurance

Descrizione del lavoro

NTT DATA is seeking an AI & Data Engineer to shape innovative AI and data solutions for clients, spanning presales, design and hands-on implementation. You will translate business needs into technical designs, build scalable data platforms and ensure production-ready deployments.

You will work directly with clients across the full lifecycle, from PoVs to handover, leveraging Generative AI, LLMs, and data lakehouse architectures while integrating with enterprise systems.

Competenze

• Degree in Computer Science, Engineering, AI, Data Science or equivalent professional experience.
• 5+ years of relevant professional experience in AI & Data Engineering or similar technical roles.
• Proven experience designing and implementing enterprise data platforms and AI solutions.

Mansioni

• Understand customer requirements from a technical and functional perspective.
• Design data and AI architectures and implement data platforms and pipelines.
• Work with clients in presales activities and workshops.
• Prepare AI-ready data layers for analytics, ML and Generative AI.
• Containerize and deploy solutions in cloud and container platforms.
• Write implementation plans and technical documentation.

Conoscenze

Python

SQL

Data pipelines

Generative AI

LLMs

Docker

Kubernetes

Cloud platforms

Data modeling

Presales

Formazione

Degree in Computer Science, Engineering, AI, Data Science or equivalent

Strumenti

Azure Data Factory

Azure Databricks

REST APIs

Git

CI/CD

Docker

Kubernetes

OpenShift

Descrizione del lavoro

NTT DATA is seeking an AI & Data Engineer to shape innovative AI and data solutions for clients, spanning presales, design and hands-on implementation. You will translate business needs into technical designs, build scalable data platforms and ensure production-ready deployments.

You will work directly with clients across the full lifecycle, from PoVs to handover, leveraging Generative AI, LLMs, and data lakehouse architectures while integrating with enterprise systems.