LLMOps Engineer

PLEASE DON’T APPLY IF YOU DON’T HAVE HANDS ON EXPERIENCE IN SETTING UP CI/CD PIPELINES AND LLMOPS IN AZURE TRACKING MODEL DRIFT AND EXPERIENCE IN MLFLOW.

Candidates who successfully pass the screening process will be required to present a portfolio of work or GitHub profile demonstrating a consistent commit history. They will also participate in a live coding session with the team.

Company Description Arada, launched in 2017 and headquartered in the UAE, focuses on creating spaces that enable healthier, happier, and more meaningful lives. The company’s operations span property development, retail, education, and hospitality, offering a diverse and dynamic environment for professionals. Arada is committed to innovative, human-centered design and sustainable community development. Team members join a growing organization that values collaboration, impact-driven work, and long-term career development.

Role Description The LLMOps Engineer role at Arada is a full-time hybrid position based in Dubai, United Arab Emirates, with flexibility for some work-from-home arrangements. In this role, you will design, build, and maintain production pipelines for large language model (LLM) applications that support various business units across property development, retail, education, and hospitality. You will be responsible for deploying and monitoring LLM services, optimizing performance, managing model versions, and ensuring reliability, security, and scalability in a cloud or hybrid infrastructure. Day-to-day activities include collaborating with data scientists and software engineers, integrating LLMs into existing systems, implementing observability and logging, and handling incident response and continuous improvement. You will also contribute to documentation, automation, and best practices that improve development efficiency and operational resilience.

Qualifications

• Strong skills in software engineering and scripting (e.g., Python, JavaScript, or similar), with experience in APIs, microservices, and integration.
• Experience with MLOps or LLMOps workflows, including model deployment, versioning, monitoring, and performance optimization.
• Hands-on experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization/orchestration tools (e.g., Docker, Kubernetes).
• Familiarity with LLMs and NLP concepts, and experience using modern AI frameworks or platforms (e.g., LangChain, OpenAI, Hugging Face, Vertex AI).
• Proficiency with CI/CD pipelines, infrastructure-as-code tools (e.g., Terraform), and observability tools (e.g., Prometheus, Grafana, ELK).
• Strong problem-solving skills, attention to detail, and ability to design robust, secure, and scalable systems.
• Effective communication and collaboration skills, with the ability to work across multidisciplinary teams and explain technical concepts clearly.
• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field; equivalent practical experience is also valued.
• Experience in real estate, retail, education, or hospitality domains, or in building data-driven products that support operational decision-making, is an advantage.