Posted on: 04/05/2026
About Zaptoz Technologies :
Working Days : 5 days/week
Role & Responsibilities :
Key Responsibilities :
- Define and implement private cloud solutions using technologies such as OpenStack and VMware
- Design scalable environments for AI/ML workloads, including training and inference pipelines
- Collaborate with data scientists, platform engineers, and infrastructure teams to translate AI requirements into infrastructure solutions
- Drive infrastructure modernization initiatives, including containerization and orchestration using Kubernetes
- Ensure high availability, performance, scalability, and security of AI platforms
- Design storage solutions optimized for AI workloads (e.g., distributed file systems, object storage)
- Implement networking architectures for high-throughput, low-latency data transfer
- Define automation strategies using Infrastructure as Code (IaC) and configuration management tools
- Establish governance, standards, and best practices for AI infrastructure and private cloud environments
- Evaluate emerging technologies and recommend solutions aligned with enterprise strategy
- Provide technical leadership and guidance across architecture, design, and implementation phases
Ideal Candidate :
- Strong Solution Architect AI Infrastructure & Private Cloud profiles
- Mandatory (Experience 1) Must have 8+years of experience in IT infrastructure, cloud, or data center architecture roles
- Mandatory (Experience 2) Must have strong expertise in private cloud and virtualization (OpenStack, VMware vSphere) along with solid knowledge of Linux, networking, and storage architectures.
- Mandatory (Experience 3) Must have hands-on experience designing AI/ML infrastructure, including GPU-based systems (e.g., NVIDIA platforms), HPC, and AI-optimized storage
- Mandatory (Experience 4) Must have strong experience with containerization and orchestration (Docker, Kubernetes) and IaC/automation tools (Terraform, Ansible)
- Mandatory (Experience 5) Must have experience designing scalable AI/ML environments for training/inference pipelines, with high-throughput, low-latency networking and distributed storage
- Mandatory (Experience 6) Must have familiarity with hybrid cloud integration (AWS, Azure, or GCP) and proven ability to lead architecture design with strong stakeholder management.
- Mandatory (Skill) Must have familiarity with hybrid cloud integration involving AWS, Azure, or GCP.
- Preferred (Skill 1) Certifications in cloud (AWS/Azure/GCP), Kubernetes, or VMware/OpenStack, along with experience in MLOps platforms and AI lifecycle management
- Preferred (Skill 2) Knowledge of high-performance networking (InfiniBand, RDMA) and exposure to data lake architectures and big data platforms
- Preferred (Skill 3) Experience in large-scale enterprise or hyperscale environments.
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Posted by
Nutanakaluva Shaik Mohammed Inamul Hassan
Senior Talent Partner at Snap Worlds
Last Active: 14 Aug 2026
Posted in
DevOps / SRE
Functional Area
ML / DL Engineering
Job Code
1632916