Key Responsibilities:
- Build enterprise-grade LLM applications using techniques such as RAG, tool calling, structured generation, prompt engineering, and agentic workflows.
- Implement and optimize LLM inference, including model serving, quantization, caching, batching, and GPU utilization where relevant.
- Develop LLM evaluation frameworks covering accuracy, relevance, hallucination, safety, latency, and cost.
- Work with open-source and commercial foundation models and assess their suitability for specific use cases.
- Build reusable components for enterprise AI applications, including knowledge retrieval, model gateways, evaluation pipelines, and agent orchestration.
Required Qualifications & Skills:
- Deploy AI/ML workloads to cloud, on-premise, and hybrid environments.
- Work with Docker, Kubernetes, GPU infrastructure, and cloud AI/ML services.
- Implement model versioning, experiment tracking, monitoring, logging, and automated deployment pipelines.
- Optimize AI workloads for scalability, reliability, latency, and cost.
- Troubleshoot production AI systems and continuously improve system performance
Education:
Bachelor's degree in computer science, Software Engineering, Computer Information Systems (CIS), AI and Data.
Professional Experience
7+ years of experience in AI Engineering.
Experience working with [Clients / Government / Consulting / GCC / Saudi market].
Soft Skills
Strong communication and presentation skills.
Strong stakeholder management and interpersonal skills.
Analytical and problem-solving capabilities.
Consulting and client-facing mindset.
Ability to work independently and collaboratively.
Strong organizational and time-management skills.
Language Requirements
- Arabic Speakers
- English
Location & Employment Details
- Location: Riyadh
- Employment Type: Full-time.