Infrastructure Engineer

Job Description

We are currently seeking a Infrastructure Engineer to join our team in Charlotte, North Carolina (US-NC), United States (US).

In This Role, You Will

• Lead complex infrastructure initiatives supporting Generative AI and Predictive AI platforms from design to production operations.
• Serve as a technical lead for platforms supporting AI/ML model training, inference, and batch workloads.
• Design, build, deploy, and operate Open Shift-based container platforms optimized for high-performance GPU workloads.
• Build, support and operate scalable GPU Super Pod architecture with large multi-node GPU clusters.
• Own monitoring, alerting, and observability using Grafana, Splunk, and enterprise telemetry tools.
• Define SLIs/SLOs and build actionable alerts to proactively detect performance, capacity, and resiliency risks.
• Build AI- and agent-based automation tools for self-healing, scaling, diagnostics, and incident remediation.
• Apply AIOps techniques to reduce alert fatigue and improve platform reliability.
• Lead production incident analysis and ensure operational rigor and root-cause prevention.
• Mentor engineers and influence stakeholders across a geographically distributed organization.

Required Qualifications

• 5+ years of infrastructure engineering experience.
• 5+ years troubleshooting complex end-to-end architectures(including CI/CD pipeline).
• 5+ years Linux systems experience.
• 4+ years supporting AI/ML platforms.
• 4+ years of Kubernetes / container platform experience including production support.

Desired Qualifications

• Experience with Generative AI and Predictive AI platforms.
• Hands‑on GPU platform operations including scheduling, quota, and performance tuning.
• Experience with Open Shift in GPU‑enabled, multi‑tenant environments.
• Experience designing or operating GPU Super Pods.
• Deep experience with observability using Grafana, Splunk, and custom telemetry pipelines.
• Experience building AI- or agent‑driven automation tooling (AIOps).
• Hands‑on experience supporting AI/ML workloads on GCP and Azure, including GPU‑backed services and managed AI infrastructure.
• Experience operating hybrid or multi‑cloud AI platforms, with an understanding of cloud‑native services, networking, identity, and cost optimization for Generative and Predictive AI.
• Strong monitoring of AI signals such as inference latency and GPU utilization.
• Experience with BCP/DR, resiliency, and highly available architectures.

Job Expectations

• Participation in a 24x7 on‑call rotation.
• Ownership for production stability, platform health, and customer outcomes.
• Operate in regulated enterprise environments with strong risk and control focus.

About NTT DATA

NTT DATA is a $30 billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start‑up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity.

We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us at

NTT DATA provides a reasonable range of compensation for U.S.

-based positions. The starting pay range for this role is 60$/hr
-65$/hr. Actual compensation will depend on a number of factors, including the candidate's relevant experience, technical skills, and other…