The company is a rapidly growing technology firm revolutionizing the field of Artificial Intelligence and Data Science, headquartered in Riyadh, Saudi Arabia. The company is committed to realizing Vision 2030, with a proven track record of excellence in supporting and growing the tech ecosystem in Saudi Arabia and the GCC region. The company serves as the trusted AI technology partner for major government organizations, corporations, and startups. We are at an exciting stage of scaling the company to provide AI-powered products and solutions both locally and globally, ensuring the growth and prosperity of our digital humanity. This is an opportunity to make a long-lasting impact in the field of AI.
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The Principal AI Engineer is a senior technical leader within the Cloud Engineering organization, responsible for shaping and standardizing the company’s approach to agentic AI systems and MLOps excellence. This role serves as a bridge between AI innovation and platform engineering, ensuring that all AI workloads (LLMs, agents, and ML models) adhere to unified, production-grade, and compliant standards for scalability, performance, and observability.
Key Responsibilities:
- Establishing and maintaining AI and agentic architecture blueprints within Cloud Engineering.
- Standardizing AI deployment practices using containerized and serverless inference patterns.
- Leading the adoption of model lifecycle management across environments (Dev → Stage → Prod).
- Collaborating with FinOps and Cloud Security to optimize cost, compliance, and control across AI workloads.
- Owning the MLOps reference stack (e.g., MLflow, Kubeflow, Ray, Vertex AI, or custom platform).
- Defining CI/CD for AI models including versioning, artifact tracking, and retraining workflows.
- Building reusable SDKs, APIs, and templates for AI pipeline integration.
- Driving model observability and monitoring standards for drift, latency, and data integrity.
- Mentoring AI and ML engineers on scalable design patterns and operational excellence.
Qualifications:
- 10+ years in software, ML, or AI engineering; 5+ years leading AI or ML systems in production.
- Expertise in Python, PyTorch/TensorFlow, and MLOps frameworks (Kubeflow, MLflow, Airflow, etc.).
- Proven experience with LLM and agentic architectures, including LangChain, vLLM, Ray, or similar.
- Familiarity with cloud-native AI stacks (Vertex AI, SageMaker, Azure AI, OCI Data Science).
- Strong understanding of distributed systems, data pipelines, and cloud orchestration.
Preferred Skills:
- Experience with vector databases (Pinecone, FAISS, Weaviate) and RAG pipelines.
- Knowledge of AI safety, fairness, and bias mitigation frameworks.
- Graduate degree (MSc/PhD) in Computer Science, Machine Learning, or a related discipline.
Key Traits:
- Platform-first thinking, ensuring AI innovations can scale reliably and securely.
- Balances deep AI knowledge with engineering pragmatism and DevOps fluency.
- Influences across domains for unified AI delivery.
- Driven by automation, repeatability, and cost-efficient AI operations.
Benefits:
- Opportunity to join a high-growth company in an exciting space with significant responsibility.
- Competitive compensation and top-tier health insurance.
- A fun and dynamic workplace alongside some of the greatest minds in AI.
- A culture that embraces diversity and empowers individuals to be their best selves.
