Machine Learning Engineer

• Create and maintain the MLOps and DevOps pipeline, ensuring deployment, monitoring, and governance of ML models.
• Build training and deployment pipelines; implement CI/CD for ML and create and maintain CI/CD pipelines (GitHub Actions, Bamboo, GitLab CI, or similar).
• Operate and evolve workloads on ECS, EKS (Kubernetes), Fargate, and managed services.
• Design, implement, and maintain AWS infrastructures using Infrastructure as Code (Terraform).
• Monitor performance and model/data drift, and implement observability practices (logs, metrics, traces) using tools like CloudWatch and Datadog.
• Integrate feature stores and environments.
• Automate operational processes using Shell scripts and Python.
• Ensure security and governance: IAM, KMS, access policies, Secrets Manager/SSM.

MLOps Engineer

AI Engineer

• Create and maintain Agent Skills for domains such as software architecture, security, data, frontend, backend, and compliance
• Define global Rules that control agent behavior across all projects
• Create Workflows that standardize the most common development cycles
• Review other Architects' Skills — ensuring instructions are clear, precise, and unambiguous for an AI agent
• Monitor real-world usage of Skills and evolve the repository based on feedback from AI Engineers
• Support onboarding of new AI Engineers — teaching how to operate the tools you created
• Stay up to date with new agentic tools, models, and ecosystem patterns

See all jobs on JobTailor

MLOps Engineer

AI Architect