AI Engineer

About Mozn MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence. We’re a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence. Our culture is built on the relentless pursuit of excellence and meaningful impact. If you’re passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises. About the role We are looking for a AI Engineer to lead the design, deployment, and optimization of machine learning and generative AI solutions. The role focuses on applying advanced ML techniques to solve real-world challenges across government and enterprise clients in Saudi Arabia. What you'll do - Designing, building, and scaling machine learning models and infrastructure - Deploying deep learning and generative models into production for public and private sector projects - Optimizing ML training and inference for performance, latency, and scalability - Monitoring, retraining, and improving deployed ML models - Driving consultation efforts, providing expert guidance to client stakeholders - Own the end-to-end delivery of AI solutions, including data pipelines, model development, backend services, APIs, integrations, user interfaces, deployment, and operations - Design and build data ingestion, transformation, and processing pipelines for structured and unstructured data - Develop backend services and APIs to expose AI capabilities securely and reliably - Build or contribute to frontend applications, dashboards, and interfaces for AI-powered solutions - Integrate AI solutions with enterprise systems, databases, authentication services, and third-party platforms Requirements - Bachelor's or master's degree in computer science or related field - 3-5 years of experience across software engineering, ML engineering, data science, data engineering and generative AI. - Strong track record of projects across public and private sectors - Expertise in Python, TensorFlow, PyTorch, ONNX, and ML deployment frameworks - Expertise in containerization and orchestration technologies (Docker, Kubernetes), with hands-on experience in ML lifecycle management (MLflow) and local LLM deployment frameworks (Ollama) - Skilled in on-premise infrastructure design and enterprise architecture frameworks, with strong adherence to security and compliance best practices - Deep understanding of hardware provisioning for local LLM deployments (GPU, RAM, and storage optimization) and secure network configurations for internal AI services - Experience with cloud ML environments (SageMaker, Vertex AI, OCI Data Science) - Familiarity with MLOps practices and automation pipelines - Strong end-to-end engineering capabilities across AI, data engineering, backend development, APIs, integrations, and application deployment - Experience building data ingestion, transformation, and processing pipelines - Familiarity with backend frameworks such as FastAPI, Flask, Django, Node.js, or equivalent technologies - Experience designing and consuming REST APIs, webhooks, and enterprise integration interfaces - Working knowledge of frontend technologies such as React, Next.js, JavaScript, TypeScript, HTML, and CSS - Experience integrating AI solutions with databases, enterprise applications, identity and access management systems, and third-party services - Ability to independently build functional AI applications from prototype through production - Experience effectively using AI-assisted software development tools to accelerate prototyping and delivery 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 AI. - We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves.

Bachelor's or Master's degree in computer science or related field. 3-5 years of experience across software engineering, ML engineering, data science, data engineering and generative AI. Strong track record of projects across public and private sectors. Expertise in Python, TensorFlow, PyTorch, ONNX, and ML deployment frameworks. Expertise in containerization and orchestration technologies (Docker, Kubernetes), with hands-on experience in ML lifecycle management (MLflow) and local LLM deployment frameworks (Ollama). Skilled in on-premise infrastructure design and enterprise architecture frameworks, with strong adherence to security and compliance best practices. Deep understanding of hardware provisioning for local LLM deployments (GPU, RAM, and storage optimization) and secure network configurations for internal AI services. Experience with cloud ML environments (SageMaker, Vertex AI, OCI Data Science). Familiarity with MLOps practices and automation pipelines. Strong end-to-end engineering capabilities across AI, data engineering, backend development, APIs, integrations, and application deployment. Experience building data ingestion, transformation, and processing pipelines. Familiarity with backend frameworks such as FastAPI, Flask, Django, Node.js, or equivalent technologies. Experience designing and consuming REST APIs, webhooks, and enterprise integration interfaces. Working knowledge of frontend technologies such as React, Next.js, JavaScript, TypeScript, HTML, and CSS. Experience integrating AI solutions with databases, enterprise applications, identity and access management systems, and third-party services. Ability to independently build functional AI applications from prototype through production. Experience effectively using AI-assisted software development tools to accelerate prototyping and delivery.

Designing, building, and scaling machine learning models and infrastructure. Deploying deep learning and generative models into production for public and private sector projects. Optimizing ML training and inference for performance, latency, and scalability. Monitoring, retraining, and improving deployed ML models. Driving consultation efforts, providing expert guidance to client stakeholders. Own the end-to-end delivery of AI solutions, including data pipelines, model development, backend services, APIs, integrations, user interfaces, deployment, and operations. Design and build data ingestion, transformation, and processing pipelines for structured and unstructured data. Develop backend services and APIs to expose AI capabilities securely and reliably. Build or contribute to frontend applications, dashboards, and interfaces for AI-powered solutions. Integrate AI solutions with enterprise systems, databases, authentication services, and third-party platforms.