MLOps & Devops Engineers📣 Job Ad

Role Overview

Devoteam is seeking MLOps & DevOps Engineers to join our team in Riyadh. This full-time role focuses on bridging the gap between data science research and AI engineering to ensure smooth Software Development Lifecycle (SDLC) delivery. The successful candidate will be responsible for designing, implementing, and maintaining the infrastructure and automated pipelines necessary for building, deploying, and monitoring modern AI platforms and RAG pipelines at scale. This position requires a deep understanding of cloud infrastructure, CI/CD practices, and the specific challenges inherent in the machine learning lifecycle.

Key Responsibilities: Infrastructure and Automation

• Design and manage scalable cloud infrastructure on Google Cloud Platform (GCP) using Terraform, with a focus on GKE clusters, firewalls, and network policies.
• Develop and maintain full SDLC CI/CD pipelines using GitHub Actions, integrating Renovate for dependency management, Sonar for code quality, and Artifactory for binary management.
• Optimize system performance and implement cost-saving measures across cloud environments.
• Build and automate end-to-end ML pipelines on Vertex AI, specializing in RAG architectures and automated data ingestion into Qdrant databases.
• Implement and manage evaluation pipelines to measure and improve the performance of LLM-based systems and agentic workflows.
• Establish automated deployment strategies for ML models, including A/B testing and Canary deployments.

Key Responsibilities: Monitoring and Reliability

• Develop comprehensive monitoring and alerting systems to ensure the health of production models and infrastructure.
• Implement data and model drift detection to maintain the accuracy of deployed models over time.
• Collaborate with security teams to ensure compliance and data privacy throughout the ML lifecycle.
• Integrate and maintain observability tools such as Langfuse, OpenTelemetry, and Prometheus to enhance system transparency and debugging for ML pipelines and LLM applications.
• Utilize distributed tracing and logging to identify bottlenecks and optimize performance across microservices and agentic workflows.

Required Experience

Candidates should possess 5 to 10 years of relevant professional experience in DevOps or MLOps engineering roles.

Work Environment

This is a full-time position based in Riyadh, Saudi Arabia, within a professional and collaborative team environment.

Application Process

Interested candidates are encouraged to apply by submitting their professional profiles for consideration.