Title: AI Infrastructure / Platform Engineer - Onsite
Mandatory skills:
Platform, Infrastructure, DevOps Engineering,
Kubernetes, container orchestration, Custom workflow tooling,
GPU compute infrastructure, powers AI, ML workloads,
software engineering, Large-scale AI training, inferencing,
orchestration systems, job status monitoring, post-mortem analysis,
APIs, self-service workflows, streamline job orchestration, networking,
CSI drivers, dynamic provisioning, CNI plugins, network policy, Infrastructure, Code tools, Terraform,
Prometheus, Grafana, Loki, machine learning frameworks, PyTorch, vLLM, SGLang
Description:
THE ROLE:
We are seeking an AI Infrastructure / Platform Engineer to join our team building and operating large-scale GPU compute infrastructure that powers AI and ML workloads. The ideal candidate should be passionate about software engineering and possess leadership skills to independently deliver on multiple projects. They should be able to communicate effectively and work optimally with their peers within our larger organization.
THE PERSON:
Experience in Platform, Infrastructure, DevOps Engineering.
Deep hands-on experience with Kubernetes and container orchestration at scale.
Proven ability to design and deliver platform features that serve internal customers or developer teams
Experience building developer-facing platforms or internal developer portals (e.g. Custom workflow tooling).
KEY RESPONSIBILITIES:
Build and extend platform capabilities to enable different classes of workloads (e.g., Large-scale AI training, inferencing etc).
Design and operate scalable orchestration systems using Kubernetes across both on-prem and multi-cloud environments.
Develop platform features such as pre-flight health checks, job status monitoring and post-mortem analysis.
Partner with development teams to extend the GPU developer platform with features, APIs, templates, and self-service workflows that streamline job orchestration and environment management.
Apply expertise in storage and networking to design and integrate CSI drivers, persistent volumes, and network policies that enable high-performance GPU workloads.
Production support on large-scale GPU clusters.
PREFERRED EXPERIENCE:
Hands-on experience in storage or network engineering within Kubernetes environments (e.g., CSI drivers, dynamic provisioning, CNI plugins, or network policy).
Experience with Infrastructure as Code tools like Terraform.
Background in HPC, Slurm, or GPU-based compute systems for ML/AI workloads.
Practical experience with monitoring and observability tools (Prometheus, Grafana, Loki, etc.).
Understanding of machine learning frameworks (PyTorch, vLLM, SGLang, etc.).
High performance network and IB/RDMA tuning.
ACADEMIC CREDENTIALS:
Bachelor’s or master''s degree in computer science, computer engineering, electrical engineering, or equivalent.
VIVA USA is an equal opportunity employer and is committed to maintaining a professional working environment that is free from discrimination and unlawful harassment. The Management, contractors, and staff of VIVA USA shall respect others without regard to race, sex, religion, age, color, creed, national or ethnic origin, physical, mental or sensory disability, marital status, sexual orientation, or status as a Vietnam-era, recently separated veteran, Active war time or campaign badge veteran, Armed forces service medal veteran, or disabled veteran. Please contact us at for any complaints, comments and suggestions.
Contact Details :
Account co-ordinator: Godwin D Antony Raj
VIVA USA INC.
3601 Algonquin Road, Suite 425
Rolling Meadows, IL 60008
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