LLMOps Engineer

Role Overview

Responsibilities

• Design, build, and maintain production pipelines for LLM applications.
• Deploy and monitor LLM services, manage model versions, and optimize performance.
• Operate services in cloud or hybrid infrastructure with attention to reliability, security, and scalability.
• Collaborate with data scientists and software engineers to integrate LLMs into existing systems.
• Implement observability and logging, handle incident response, and support continuous improvement.
• Contribute to documentation, automation, and practices that improve development efficiency and operational resilience.

Qualifications

• Hands-on experience with CI/CD pipelines and LLMOps in Azure, including model drift tracking and MLflow.
• Strong software engineering and scripting skills using Python, JavaScript, or a similar language, plus APIs, microservices, and integration.
• Experience with MLOps or LLMOps model deployment, versioning, monitoring, and performance optimization.
• Hands-on experience with cloud platforms and containerization or orchestration tools.
• Familiarity with LLMs, NLP concepts, and modern AI frameworks or platforms.
• Proficiency with infrastructure as code and observability tools.
• Strong problem-solving, system design, communication, and collaboration skills.
• A bachelor’s degree in a related field or equivalent practical experience is valued.
• Relevant real estate, retail, education, hospitality, or operational product experience is advantageous.

Assessment Process

• Candidates who pass screening must present a portfolio or GitHub profile showing a consistent commit history.
• Candidates who pass screening must participate in a live coding session.

Work Arrangement

• The role is full-time and hybrid in Dubai, with flexibility for some work-from-home arrangements.