Technology Platform Engineer

TymblHub; Gurugram District; On-site; INR 3,000,000 - 5,500,000; Full time

Job summary

TymblHub is seeking a Technology Platform Engineer to design and operate HPC and AI infrastructure across on-prem, cloud, and hybrid environments. The role involves building production and non-production cloud environments, deploying automation pipelines, and enabling scalable MaaS/GPUaaS/AIaaS offerings.

The candidate will work with Linux-based architectures, GPUs/XPUs, and modern orchestration tools, while optimizing performance and cost and contributing to architecture runbooks and user

Qualifications

• Experience in enterprise-wide HPC strategy and architecting next-gen supercomputing environments across the full stack.
• Primary Skills: Linux Administrator/Architect, Advanced CUDA/GPU on H100/A100, HPC cluster design (SLURM/PBS Pro).
• Secondary Skills: Parallel programming MPI/OpenMP/CUDA; HPC integration (Kubeflow); containerization (Kubernetes, Docker); DevOps: Ansible, Terraform for HPC.

Responsibilities

• Design and implement HPC and AI infrastructure solutions, aligning architecture to performance and scalability needs.
• Deploy, configure, and manage XPU-based clusters (CPU/GPU/accelerators) using schedulers, VM/K8s orchestration, Slurm, and container platforms.
• Optimize cluster performance, scalability, energy, and cost efficiency across on‑premises, cloud, and hybrid environments.
• Integrate AI and HPC platforms with IT systems, data pipelines, and security frameworks.
• Monitor, troubleshoot, and tune infrastructure for high availability and low-latency networking.
• Develop and maintain documentation including architecture diagrams, baselines, and runbooks; provide user guidance.

Skills

Linux Administrator/Architect

CUDA/GPU on H100/A100

HPC cluster design

Kubernetes

Docker

Terraform

Ansible

Education

15 years full time education

Tools

SLURM

Singularity

RunAI

NVIDIA CUDA

Job description

## Job Description## Job Summary**Project Role:** Technology Platform Engineer**Project Role Description:** Creates production and non-production cloud environments using the proper software tools such as a platform for a project or product. Deploys the automation pipeline and automates environment creation and configuration.**Must have skills:****Linux Architecture****Good to have skills:****Machine Learning (ML)**, **Cloud Technology Architecture**, **Docker Kubernetes Administration**, **Edge Computing**, **Microsoft Agentic AI Architect****Experience:** Minimum 5 Year(s) Of Experience Is Required**Educational Qualification:** 15 years full time education## Key Responsibilities* Design and implement HPC and AI infrastructure solutions, aligning system architecture and deployment roadmaps to industry-specific performance and scalability needs* Deploy, configure, and manage XPU-based clusters (CPU/GPU/accelerators) using schedulers, VM/K8s orchestration platforms, Slurm, and containerized platforms in scalable designs to provide Metal as a Service (MaaS), GPUaaS, AIaaS, and other offerings* Optimize cluster performance, scalability, energy, and cost efficiency across on-premises, cloud, and hybrid environments* Integrate AI and HPC platforms with existing IT systems, data pipelines, and security frameworks* Monitor, troubleshoot, and tune infrastructure to ensure high availability, low-latency networking, and workload resiliency* Develop and maintain documentation including architecture diagrams, configuration baselines, and operational runbooks* Provide technical guidance and support to users, enabling efficient execution of HPC/AI workloads, large-scale models, and simulations## Requirements### Required Skills and Qualifications* Experience in enterprise-wide HPC strategy and architecting next-gen supercomputing environments across the full stack.* Primary Skills: **Linux Administrator/Architect**, Advanced **CUDA/GPU on H100/A100**, HPC cluster design (SLURM/PBS Pro)* Secondary Skills: Parallel programming: MPI, OpenMP, CUDA, SYCL, **NVIDIA DGX SuperPOD & BCM**, InfiniBand NDR 400Gb/s & RoCEv2 design, MLOps & HPC integration (Kubeflow), Containerization: Singularity, **Kubernetes**, DevOps: **Ansible**, **Terraform** for HPC, UFM management, RunAI, Azure ML integration: distributed training, MLflow, Terraform / Bicep IaC for Azure HPC, FinOps: Reserved Instances, Spot VM strategies, Hybrid cloud HPC: on-prem to Azure/AWS burst* Proven hands-on experience designing, deploying, and managing HPC and AI infrastructure across on-premises, cloud, and hybrid environments in 2 or more segments: hyperscaler, neocloud, large Enterprise, Telco/Mobile, supporting key industries such as Financial Services, Life Sciences, Manufacturing, and Retail* Deep knowledge of accelerated computing architectures (GPUs, XPUs, DPUs), high-performance fabrics (InfiniBand, Ethernet), SONiC, networking, and modern storage/data platforms (e.g. NVMe-oF, Lustre, GPFS, BeeGFS, VAST, DDN, Weka) to build robust solutions* Proficiency with cluster management and orchestration (e.g. Slurm, Run:ai, **Kubernetes**, **Docker**), real-time performance monitoring, and observability frameworks* Hands-on experience with cloud and virtualization platforms (e.g. AWS, Azure, GCP, VMware, Nutanix) and expertise in automation and optimization using scripting (Python, AI tools) with foundational Infrastructure-as-Code tools such as **Terraform** and **Ansible**.### Preferred Skills and Qualifications* Experience managing the deployment of 1,000+ GPU clusters for HPC and AI workloads with various infrastructure services enabled* Experience with GPU computing libraries and accelerators (e.g., NVIDIA CUDA, Dynamo, AMD ROCm).* Experience with AI and HPC Networking (e.g., RoCE, InfiniBand, muti-planar/multi-rail designs, platform buffer architectures)* Knowledge of **Machine Learning** and AI frameworks (e.g., TensorFlow, PyTorch, JAX), Jupyter notebooks / Google Colab environments* Familiarity with DevOps practices and tools (e.g., Ansible, Terraform) for infrastructure automation* Experience with **AgenticAI** and associated technologies to leverage and build agents for workflow automation and observability* Industry certifications in NVIDIA infrastructure, public cloud providers, Data Science, etc. are a plus* Strong problem-solving, troubleshooting, communication, and collaboration skills to deliver reliable, scalable, and high-performance infrastructure solutions in fast-paced, dynamic environments that reward technical talent