MLOps / AI Platform Engineer

About the role

Join Aumnitech as an MLOps / AI Platform Engineer to operationalize AI solutions, ensuring reliable deployment, monitoring, cost control, and governance for models and large‑language‑model (LLM) applications in production.

Key responsibilities

• Design and implement CI/CD pipelines for model and LLM application deployment.
• Establish monitoring, versioning, and rollback mechanisms for AI workloads.
• Manage cost, latency, and reliability of production AI services.
• Implement governance controls, including access management, audit logging, and usage tracking.
• Collaborate with the security team to meet AI‑specific compliance requirements.
• Support multi‑cloud AI infrastructure across AWS, Azure, and GCP.

Required profile

• 4+ years of experience in DevOps or platform engineering, with at least 1–2 years focused on ML/AI systems.
• Proficiency with Kubernetes, Docker, and Terraform (or equivalent IaC tool).
• Familiarity with MLOps platforms such as MLflow, Kubeflow, SageMaker, or Vertex AI.
• Strong scripting skills in Python or Go and hands‑on CI/CD pipeline development.
• Solid understanding of model versioning, monitoring, and cost‑optimization practices.

Required skills

• Kubernetes
• Docker
• Terraform (or similar IaC)
• MLflow
• Kubeflow
• SageMaker
• Vertex AI
• Python
• Go
• CI/CD pipelines
• AWS
• Azure
• GCP