Join NTT DATA as a Senior AI Platform & GPU-as-a-Service (GPUaaS) Engineer in Hyderabad. This role focuses on building, managing, and optimizing enterprise AI platforms, including capabilities for AI, Generative AI (GenAI), Machine Learning (ML), Large Language Models (LLMs), High Performance Computing (HPC), and GPU-accelerated workloads.

You will collaborate with various teams, including architecture, infrastructure, security, networking, and business units, to deliver a robust and secure GPU platform that supports scalable AI adoption across the enterprise. The position involves platform engineering, customer onboarding, GPU workload enablement, operational readiness, observability, capacity management, and service optimization.

We seek an individual with a strong blend of platform engineering expertise, operational experience, automation skills, and customer engagement capabilities. The ideal candidate is adept at working across infrastructure, platforms, AI workloads, automation, and operations to transform GPU infrastructure into an enterprise-grade GPU-as-a-Service offering.

Develop, operate, automate, and optimize the enterprise AI Platform & Acceleration Services (AIPAS) capability. Partner with cross-functional teams to deliver a production-ready, scalable, and secure GPU platform for enterprise AI adoption.

Support key functions including platform engineering, customer onboarding, GPU workload enablement, operational readiness, observability, capacity management, automation, self-service capabilities, and service optimization. Ensure a seamless experience for users of the GPU platform.

Drive transformation of GPU infrastructure into an enterprise GPU-as-a-Service offering, balancing infrastructure, platform, AI workload, automation, and operational considerations.

A Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent practical experience is required.

Demonstrate 5+ years in Platform Engineering, Infrastructure Engineering, Cloud Engineering, or Site Reliability Engineering (SRE). Possess 3+ years of experience with Kubernetes and/or OpenShift, alongside experience in operating enterprise production platforms and automating infrastructure.

Familiarity with Machine Learning and Large Language Models (inferencing and fine-tuning) is essential. Experience working across diverse technology teams (infrastructure, security, application, operations) and with NVIDIA GPU infrastructure is also necessary.