The company is seeking a highly skilled MLOps/DevOps Engineer to bridge the gap between data science research and AI engineering, ensuring smooth Software Development Life Cycle (SDLC) delivery. In this role, you will be responsible for designing, implementing, and maintaining infrastructure and automated pipelines that enable our teams to build, deploy, and monitor modern AI platforms and Retrieval-Augmented Generation (RAG) pipelines at scale.
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Key Responsibilities:
Infrastructure and Automation:
- Design and manage scalable cloud infrastructure on Google Cloud Platform (GCP) using Terraform, focusing 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.
- Build and automate end-to-end ML pipelines on Vertex AI, specializing in RAG architectures and automated data ingestion into Qdrant databases.
- Establish automated deployment strategies for ML models, including A/B testing and Canary deployments.
Monitoring and Reliability:
- Develop comprehensive monitoring and alerting systems to ensure the health of production models and infrastructure.
- 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.
Qualifications:
- Experience: 3+ years in DevOps, SRE, or MLOps roles.
- Proficiency in Google Cloud Platform (GCP).
- Advanced knowledge of Docker and Kubernetes (GKE).
- Expertise in Python, GitHub Actions, Renovate, Sonar, Artifactory, Argo CD, and Helm charts.
- Experience with SQL, NoSQL databases, and data orchestration tools (Airflow).
Preferred Skills:
- Experience with Vertex AI, RAG pipelines, Qdrant, and LLM orchestration (LangChain or LlamaIndex).
- Contributions to open-source DevOps or MLOps projects.
- Relevant certifications (e.g., AWS Certified DevOps Engineer, CKA).
Additional Information:
- Business Unit: Data & Intelligence
- Level: Mid - Senior Level
- Work Conditions: On-site, Full-time
- Location: Riyadh, Riyadh, Saudi Arabia
