AI Infra & SRE Engineer - Data Center Scale

Qualcomm; Riyad Al Khabra; On-site; SAR 450,000 - 900,000; Full time

Benefits offered by this job

Housing & transport allowance

RSU stock & performance bonus

14–16 weeks maternity leave

Paternity leave

Job summary

Qualcomm Middle East Information Technology Company LLC is seeking an experienced Software Test Engineer focused on AI infrastructure and datacenter AI workloads. You will design, deploy, and refine large-scale AI inference systems, ensuring reliability, scalability, and production readiness across multi‑card environments.

The role requires hands-on execution and collaboration across hardware, software, and ML teams.

Qualifications

• Bachelor’s or Master’s degree in Engineering, Information Systems, Computer Science, or related field.
• 6+ years in Software Test Engineering or related work experience.
• Experience with AI/ML workloads, LLMs, NLP, or similar domains.
• Experience with production AI/ML services and MLOps concepts.
• Strong Python programming and automation scripting (Python/Bash).
• Familiarity with CI/CD pipelines and configuration management tools.

Responsibilities

• Define, deploy, and operate large-scale AI inference systems in a datacenter environment.
• Ensure reliability, availability, and scalability of AI clusters.
• Develop tools and support infrastructure around AI software stacks.
• Support AI/ML workloads across models, systems, and services.
• Improve model performance on multi‑SoC and multi‑card deployments.
• Apply SRE practices: monitoring, incident response, and runbooks.

Skills

AI & ML workloads

PyTorch

Distributed inference

Python programming

Linux fundamentals

CI/CD

Education

Bachelor’s degree in Engineering/CS/IS or related field

Master’s degree (preferred)

PhD (optional)

Tools

Terraform

Ansible

Prometheus

Grafana

Kubernetes

ELK / Loki

Job description

Qualcomm Middle East Information Technology Company LLC is seeking an experienced Software Test Engineer focused on AI infrastructure and datacenter AI workloads. You will design, deploy, and refine large-scale AI inference systems, ensuring reliability, scalability, and production readiness across multi‑card environments.

The role requires hands-on execution and collaboration across hardware, software, and ML teams.