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About / Author

Gowtham Ramu

I have spent 20+ years building and operating infrastructure across datacenters, cloud platforms, and now AI-native stacks. Today, my work focuses on helping teams run NVIDIA-centric environments with operational clarity, strong fundamentals, and production discipline.

Infrastructure operator, architect, and trainer focused on making AI platforms reliable, efficient, and production-ready.

20+ years in infrastructure 3000+ engineers enabled NVIDIA NCP x4 AWS x13

What I Do

I work at the intersection of infrastructure architecture and real-world operations. My focus is to turn complex platform strategy into systems that engineering teams can run with confidence under load, failure, and constant change.

  • NVIDIA-centric AI infrastructure operations and engineering readiness
  • GPU platform reliability, utilization, and failure-mode troubleshooting
  • Kubernetes, Slurm, and infrastructure orchestration for AI workloads
  • Training and mentoring engineers moving from traditional infrastructure to AI infrastructure roles

Career Timeline

  1. 2018 to 2025

    Director / Senior Manager, Cloud, Data and Platform Engineering

    Deloitte, Seattle

    Built cloud-native data and compute foundations for AI and analytics workloads across AWS, Azure, and GCP. Led platform engineering across Kubernetes, networking, security, identity, and distributed systems.

  2. 2015 to 2017

    Principal Cloud and Platform Consultant

    UST Global (Client: T-Mobile), USA

    Led large-scale platform migrations, applied AWS Well-Architected standards, and operated early Kubernetes platforms with IaC automation and governance.

  3. 2012 to 2014

    Cloud Leader / Infrastructure Lead

    IBM, Australia

    Owned Linux and UNIX operations for 2,800+ mission-critical systems, led service continuity programs, and introduced early hybrid cloud patterns in regulated environments.

  4. 2010 to 2011

    Cloud Consultant

    Deakin University, Australia

    Delivered private-cloud and virtualization programs, including large migration waves and production build standards for Linux and Windows workloads.

  5. 2001 to 2009

    Senior Infrastructure and Systems Roles

    Sun Microsystems, ANZ Bank, Wipro, and others

    Built deep systems foundations in Solaris, Linux, storage, and datacenter operations under strict uptime, performance, and escalation requirements.

Selected Outcomes

  • Enabled 3,000+ practitioners to transition into hands-on cloud, data, and platform engineering roles.
  • Presented at AWS re:Invent to 500+ attendees and published technical breakout content.
  • Scaled cloud footprints from early adoption stages into large enterprise estates with governance and reliability controls.
  • Delivered platform modernization across telecom, financial services, higher education, media, and public sector workloads.
  • Built operating models that connect architecture decisions to day-2 execution, incident response, and cost discipline.

Certifications and Technical Depth

  • NVIDIA Certified Professional: AI Infrastructure, AI Operations, AI Networking, Accelerated Data Science (NCP-ADS)
  • AWS: 13 certifications including Professional and Specialty tracks
  • Databricks Certified Data Engineer Professional
  • Kubernetes: CKA and cloud-native certifications
  • TOGAF 9, Terraform Associate, Vault Associate, FinOps Practitioner

Why dcops.ai

The next wave of AI success will be decided by infrastructure execution, not only model innovation. dcops.ai exists to train engineers who can operate GPU platforms with precision, make better decisions under pressure, and convert infrastructure spend into reliable outcomes.