Platform Deployment Engineer (AI Factory Delivery)

Sharon AI, Inc; Abu Dhabi; Remote; AED 320,000 - 520,000; Full time

Benefits offered by this job

Birthday leave

Employee Assistance Program (EAP)

Learning & development opportunities

Global projects in UAE and beyond

Job summary

Sharon AI, Inc. is seeking a Platform Deployment Engineer in the UAE remote delivery squad to deploy and manage AI Factory platform layers.

You will orchestrate Kubernetes clusters with GPU nodes, deploy NVIDIA operators, and enable self-service provisioning while ensuring performance and security at scale. You will collaborate with cross-functional teams including Network, Infra, Platform, and Operations, handling testing, handover, and on-call support during hypercare.

Qualifications

• Bachelor's degree in Computer Science or a related field is required.
• Proven experience with Kubernetes and GPU workloads in production.
• Strong scripting and programming skills in Python, Go or Bash.

Responsibilities

• Bring each AI Factory under Rafay and stand up/tune Kubernetes clusters with GPU nodes.
• Deploy NVIDIA GPU Operator and other platform components in a version-locked fashion.
• Configure workload scheduling, resource allocation, and multi-tenant security.
• Configure/validate self-service APIs, CLI and portal access for GPU provisioning.
• Plan and execute platform testing including ATP and IST, GPU benchmarks.
• Support customer site acceptance testing and fix defects pre-handover.
• Work with on-site staff and data centre for physical tasks as needed.
• Deliver repeatable deployments using Ansible and Terraform, with IaC tooling.
• Feed lessons learned into standard playbooks and platform designs.
• Prepare handover docs, runbooks, and knowledge transfer to Operations.
• Support Operations during hypercare and report progress/risks to Regional Delivery Manager.

Skills

Kubernetes

GPU workloads

Cloud-native infra

Ansible

Terraform

Python

Go

Bash

CI/CD

Infra automation

Stakeholder management

Prioritization

Collaboration

Attention to detail

AI interest

Rafay

GPU HPC

PyTorch

TensorFlow

MLOps tools

Education

Bachelor's degree in Computer Science or related field

Tools

Rafay

Job description

️ Full-time | Permanent | Start ASAP

United Arab Emirates (UAE) – Remote

UAE-based remote working

About Sharon AI

Sharon AI is a neocloud, delivering trusted AI infrastructure organisations need to build, train and run AI at scale. We support customers across the full AI lifecycle, from training through to inference and agentic AI, drawing on a strong ecosystem of technology and co-location partners to deliver capability where it's needed. As the first neocloud to join NVIDIA's AI Compute Program, we're growing quickly, scaling our AI Factory platform to meet rising demand for advanced compute.

The Role

As Sharon AI continues to grow, we're looking for a talented Platform Deployment Engineer to join our UAE Delivery squad and play an important role in deploying and delivering the platform layer of our AI Factories, reporting to our Regional Delivery Manager.

AI Factories are the high-performance GPU compute environments that underpin Sharon AI's AI cloud, serving customers and internal teams running large-scale training, fine-tuning and inference. In this role, the Platform Deployment Engineer will take the orchestration, scheduling and self-service layer of each AI Factory from build through to customer acceptance, so the platform is ready for customers and for Operations from day one. You'll both deploy and test, and look for ways to make each deployment faster than the last. You'll work closely with Network and Infrastructure Deployment Engineers, on-site Data Centre Deployment Engineers, the Platform team and Operations, with exposure to cutting-edge technology at the forefront of AI infrastructure.

What You'll Be Doing

• Bringing each AI Factory under Rafay, and standing up and tuning Kubernetes clusters (and Slurm where used) with GPU nodes to meet agreed design and performance targets
• Deploying the NVIDIA GPU Operator and other platform components at the version-locked set
• Configuring workload scheduling, resource allocation, and multi-tenant security and isolation in line with each AI Factory's design
• Configuring and validating self-service APIs, CLI and portal access for GPU provisioning, and integrating observability and monitoring so each AI Factory is visible to Operations from day one
• Planning and executing platform testing, including acceptance testing (ATP), integrated system testing (IST), GPU performance and NCCL benchmarks, and multi-hour training jobs across the cluster
• Supporting customer site acceptance testing, recording results against pass/fail thresholds and fixing defects before handover
• Working with on-site staff and the data centre provider's remote hands for any physical task, such as reseating, part swaps or console access
• Delivering repeatable deployments using infrastructure-as-code (Ansible and Terraform) and shared deployment scripts, timing each step and proposing changes that shorten the cycle
• Feeding lessons learned back into standard playbooks and tooling, and to the Platform team for its designs and configurations
• Preparing handover documentation, runbooks and as-built records, and transferring knowledge to Operations and the Platform team
• Supporting Operations during the hypercare window (up to one month), on call for build defects, and reporting progress, risks and issues to the Regional Delivery Manager

What We're Looking For

• 4 to 8+ years' experience in platform engineering or SRE
• Strong experience with Kubernetes and GPU workloads in production
• Experience working with cloud-native infrastructure at scale
• Strong experience with Ansible and Terraform, and programming in Python, Go or Bash
• Experience with CI/CD and infrastructure automation
• Bachelor's degree in Computer Science or a related field
• Strong communication and stakeholder management skills
• Ability to manage competing priorities in a fast-paced environment
• A proactive, collaborative and solutions-focused approach
• Strong attention to detail
• A genuine interest in AI, technology and what Sharon AI is building

Nice to have:

• Rafay or similar multi-cluster platform experience
• GPU cloud or HPC platform experience, and GPU technologies such as CUDA and NCCL
• ML frameworks (PyTorch, TensorFlow) and MLOps tools (Ray, Kubeflow, Airflow)
• CKA or cloud certifications

Why Join Sharon AI?

You'll be joining a rapidly growing technology business at an exciting stage of its journey, with the opportunity to work directly with the infrastructure and technology powering the next generation of AI.

UAE-based remote working – work from wherever suits you, in the same time zone as your squad

Birthday leave – take some extra time to celebrate your day

Employee Assistance Program (EAP) – confidential support when you need it

Exposure to AI and next-generation technology – work in one of the fastest-moving areas of technology

Learning & development – we support your career growth with approved conferences, professional memberships & courses

Work on leading-edge AI infrastructure projects in the UAE

Bounty referral program – generous rewards for successfully referring new talent to Sharon AI

Employee of the month – recognition plus a $500 gift card

Growing global business – be part of an technology company with an expanding international footprint

Make an impact – join at a stage where your work can have a visible influence on how we build and grow

Collaborative culture – work alongside talented people across technical, commercial and corporate teams

Our Values

Integrity | Innovation | Collaboration | Wellbeing | Inclusion

Due to the high volume of applications we receive, we're unfortunately not always able to provide individual feedback to unsuccessful candidates. We appreciate your understanding and want to assure you that every application will be reviewed with care.