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Principal AI Engineer

Job in Riyadh, Riyadh Region, Saudi Arabia
Listing for: Mozn
Full Time position
Listed on 2025-12-02
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Cloud Computing, Data Engineer
Salary/Wage Range or Industry Benchmark: 200000 - 300000 SAR Yearly SAR 200000.00 300000.00 YEAR
Job Description & How to Apply Below

About Mozn
Mozn is a rapidly growing technology firm revolutionizing the field of Artificial Intelligence and Data Science headquartered in Riyadh, Saudi Arabia. The company works to realize Vision 2030 with a proven track record of excellence in supporting and growing the tech ecosystem in Saudi Arabia and the GCC region. Mozn is the trusted AI technology partner for some of the largest government organizations, as well as many large corporations and startups.

We are in an exciting stage of scaling the company to provide AI‑powered products and solutions both locally and globally that ensure the growth and prosperity of our digital humanity. It is an exciting time to work in the field of AI to create long‑lasting impact.

About The Role
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 bridges AI innovation and platform engineering – ensuring that all AI workloads (LLMs, agents, and ML models) follow unified, production‑grade, and compliant standards for scalability, performance, and observability.

What You’ll Do
  • Establish and maintain AI and agentic architecture blueprints (RAG, orchestration, fine‑tuning, prompt pipelines, etc.) within Cloud Engineering
  • Standardize AI deployment practices using containerized and serverless inference patterns
  • Lead the adoption of model lifecycle management across environments (Dev → Stage → Prod)
  • Partner with Fin Ops and Cloud Security to optimize cost, compliance, and control across AI workloads
  • Own the MLOps reference stack (e.g., MLflow, Kubeflow, Ray, Vertex AI, or custom platform)
  • Define CI/CD for AI models including versioning, artifact tracking, and retraining workflows
  • Build reusable SDKs, APIs, and templates for AI pipeline integration with Cloud Engineering systems
  • Drive model observability and monitoring standards for drift, latency, and data integrity
  • Lead the design and enablement of agentic AI systems (LLM‑driven orchestrators, tool‑using agents, multi‑agent frameworks)
  • Create reference implementations and governance frameworks for RAG, memory, and action‑based AI workflows
  • Collaborate with product and data teams to move prototypes into secure, production‑grade environments
  • Embed AI security, data protection, and PDPL/GDPR compliance into the MLOps lifecycle
  • Define model validation and explainability standards, ensuring auditability and traceability
  • Work with Cloud Security and Data teams on responsible AI controls and AIOps monitoring
  • Mentor AI and ML engineers on scalable design patterns and operational excellence
  • Contribute to internal AI guilds, tech councils, and engineering playbooks
  • Represent Cloud Engineering in AI ecosystem evaluations and cross‑functional initiatives
Qualifications
  • 10+ years in software, ML, or AI engineering; 5+ years leading AI or ML systems in production
  • Expert in Python, PyTorch/Tensor Flow, and MLOps frameworks (Kubeflow, MLflow, Airflow, etc.)
  • Proven experience with LLM and agentic architectures, including Lang Chain, vLLM, Ray, or similar
  • Experience with cloud‑native AI stacks (Vertex AI, Sage Maker, Azure AI, OCI Data Science)
  • Strong understanding of distributed systems, data pipelines, and cloud orchestration (Kubernetes, GKE, EKS, AKS)
  • Track record of defining AI infrastructure standards in large or multi‑tenant SaaS environments
Preferred Skills
  • Hands‑on with vector databases (Pinecone, FAISS, Weaviate) and RAG pipelines
  • Familiarity with AI cost optimization, GPU utilization metrics, and inference scaling
  • Knowledge of AI safety, fairness, and bias mitigation frameworks
  • Graduate degree (MSc/PhD) in Computer Science, Machine Learning, or a related discipline
Key Traits
  • Thinks platform‑first, ensuring every AI innovation can scale reliably and securely
  • Balances deep AI knowledge with engineering pragmatism and Dev Ops fluency
  • Influences across domains – from MLOps to Cloud to Security – to enable unified AI delivery
  • Obsessed with automation, repeatability, and cost‑efficient AI operations
Benefits
  • At the forefront of an exciting time for the Middle East, joining a high‑growth rocket‑ship
  • Granted significant responsibility and trust, with freedom to shape the role
  • Competitive compensation, top‑tier health insurance, and an enabling culture to focus on your strengths
  • A fun and dynamic workplace working alongside some of the greatest minds in AI
  • Embraces diversity, empowering each person to be their best self

Seniority Level
:
Mid‑Senior level

Employment Type
:
Full‑time

Job Function
:
Engineering and Information Technology

Industries
:
Software Development

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