Principal AI Engineer

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October 22

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Mozn

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Artificial Intelligence • SaaS • Enterprise

Mozn is a regional AI company building Arabic-native generative AI and enterprise AI platforms. It provides OSOS (an Arabic-first GenAI platform), FOCAL (a financial-crime and fraud detection platform), and customized AI solutions spanning language intelligence, risk intelligence, operational AI, data management, geospatial intelligence, and AI centers. Mozn focuses on serving enterprise customers in the MENA region (including healthcare, finance, and government) with SaaS products and tailored AI services that prioritize cultural relevance, data security, and regulatory compliance.

201 - 500 employees

Founded 2017

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

💰 $10M Series A on 2022-02

📋 Description

• Establishing and maintaining AI and agentic architecture blueprints (RAG, orchestration, fine-tuning, prompt pipelines, etc.) 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) • Partnering 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 with Cloud Engineering systems • Driving model observability and monitoring standards for drift, latency, and data integrity • Leading the design and enablement of agentic AI systems (LLM-driven orchestrators, tool-using agents, multi-agent frameworks) • Creating reference implementations and governance frameworks for RAG, memory, and action-based AI workflows. • Collaborating with product and data teams to move prototypes into secure, production-grade environments • Embedding AI security, data protection, and PDPL/GDPR compliance into the MLOps lifecycle • Defining model validation and explainability standards, ensuring auditability and traceability • Working with Cloud Security and Data teams on responsible AI controls and AIOps monitoring • Mentoring AI and ML engineers on scalable design patterns and operational excellence • Contributing to internal AI guilds, tech councils, and engineering playbooks. • Representing Cloud Engineering in AI ecosystem evaluations and cross-functional initiatives

🎯 Requirements

• 10+ years in software, ML, or AI engineering; 5+ years leading AI or ML systems in production • Expert in Python, PyTorch/TensorFlow, and MLOps frameworks (Kubeflow, MLflow, Airflow, etc.) • Proven experience with LLM and agentic architectures, including LangChain, vLLM, Ray, or similar • Experience with cloud-native AI stacks (Vertex AI, SageMaker, 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 • Graduate degree (MSc/PhD) in Computer Science, Machine Learning, or a related discipline

🏖️ Benefits

• You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space • You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best • The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best • You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in Al • We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves