Lead MLOps Architect – AWS

Experience: 1012 Years
Location: Egypt (Onsite Role)
Employment Type: Full-Time

We are seeking a highly experienced Lead MLOps Architect with deep AWS expertise to lead the design architecture and governance of enterprise-grade ML platforms. This role requires strong leadership capabilities hands-on expertise in scalable ML systems and experience managing large production environments.

• Architect and lead enterprise-scale MLOps platforms on AWS
• Define best practices for ML lifecycle management deployment standards and governance
• Lead production deployment of ML models using AWS-native services
• Design automated CI/CD pipelines for ML workflows and infrastructure
• Implement advanced monitoring drift detection retraining automation and observability
• Ensure high availability scalability security and cost optimization
• Establish model versioning reproducibility and experiment tracking standards
• Lead troubleshooting of complex production issues
• Mentor and lead a team of MLOps and platform engineers
• Collaborate with stakeholders to align ML platform strategy with business objectives

• 1012 years of overall experience with strong focus on ML production systems
• Proven experience leading ML platform architecture and large-scale deployments
• Deep understanding of ML lifecycle management governance and reproducibility
• Hands-on experience with TensorFlow PyTorch Scikit-learn
• Strong experience with MLflow or enterprise model management tools

• Advanced hands-on expertise in:
  • Amazon SageMaker (training pipelines endpoints)
  • S3 EC2 Lambda
  • ECR ECS EKS
  • IAM CloudWatch
• Experience designing secure compliant and scalable ML architectures
• Experience implementing cost optimization strategies on AWS

• Strong expertise in Docker and Kubernetes (EKS)
• Advanced CI/CD implementation
• Infrastructure as Code using Terraform and/or CloudFormation
• Experience implementing GitOps practices

• Expert-level Python skills
• Experience designing robust data pipelines
• Strong understanding of SQL/NoSQL systems
• Exposure to streaming or real-time ML systems

• AWS Professional-level certifications
• Experience with ML security explainability and regulatory compliance
• Experience building enterprise feature stores
• Exposure to real-time inference systems