Principal AI Engineer at Mozn

Dubai, Dubai, United Arab Emirates -

Full Time

Start Date

Immediate

Expiry Date

17 Jan, 26

Salary

0.0

Posted On

19 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, PyTorch, TensorFlow, MLOps, LLM, Agentic Architectures, Cloud-Native AI Stacks, Distributed Systems, Data Pipelines, Cloud Orchestration, AI Infrastructure Standards, Vector Databases, AI Cost Optimization, AI Safety, Fairness, Bias Mitigation

Industry

Software Development

Description

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. You will define the blueprints, frameworks, and reference architectures for AI workloads across all product lines, partnering closely with AI researchers, data scientists, and platform engineers to enable secure, efficient, and repeatable AI delivery. What you'll do 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 Qualifications 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 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 DevOps 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 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

Responsibilities

The Principal AI Engineer will shape and standardize the company’s approach to agentic AI systems and MLOps excellence. This role involves defining blueprints and frameworks for AI workloads and ensuring compliance with production-grade standards.