AI Systems Engineer

Qualifications & Experience

• Bachelor’s or Master’s degree in Computer Engineering, Computer Science, Artificial Intelligence, or a related field.
• 4+ years of hands-on experience in AI/ML systems engineering, machine learning infrastructure, or performance engineering.
• Proven experience evaluating and deploying AI/ML runtimes, inference frameworks, or model optimization techniques.
• Experience working with model compression, quantization, or efficient on-device/edge inference.
• Strong background in building or integrating backend systems, runtime components, or distributed software.
• Practical experience with PyTorch, ONNX Runtime, TensorFlow, or other ML frameworks.
• Solid programming expertise in Python and at least one systems-level language (C++, C#, Go, or Rust).
• Experience taking AI-enabled solutions from research or prototype stage to production is highly desirable.
• Familiarity with DevOps tools, CI/CD pipelines, and containerization (e.g., Docker) is a plus.

Skills / Knowledge

• Strong understanding of AI/ML system design, model execution pipelines, and optimization techniques.
• Ability to evaluate performance trade-offs across different hardware architectures (CPU, GPU, NPU).
• Skilled in benchmarking, profiling, and optimizing AI workloads.
• Knowledge of secure software development practices and data handling principles.
• Ability to design scalable, maintainable system components and integration layers.

Professional Competencies

• Excellent analytical thinking and problem-solving capability.
• Ability to translate research findings into practical engineering decisions.
• Strong communication skills , able to explain technical concepts to both technical and non-technical stakeholders.
• High level of ownership and initiative; able to drive complex technical initiatives with minimal supervision.
• Strong collaboration skills with cross-functional teams (product, DevOps, infrastructure, security).
• Detail-oriented with strong documentation and technical reporting abilities.
  
  

Language Requirements

• English (fluent written and verbal) – Mandatory

• Arabic (fluent written and verbal) – Mandatory

To lead the technical research, architecture design, and engineering supervision for a new AI-driven product initiative. This role will be responsible for evaluating modern AI technologies, designing core system components, and guiding the engineering team from early prototypes to a production-ready platform.

• Research and evaluate AI runtimes, model optimization techniques, and deployment frameworks.
• Design the technical architecture of the solution, including core runtimes, integration layers, and update mechanisms.
• Build and validate prototypes to benchmark performance across different hardware and software stacks.
• Work with development teams to transform prototypes into stable, scalable, and secure production software.
• Define engineering standards, testing approaches, and CI/CD pipelines.
• Collaborate with product, DevOps, and security teams to ensure alignment and compliance.
• Produce high-quality documentation, architecture diagrams, and technical reports.