MLOps & Agentic Platform Engineer (AI Infrastructure)

📋 Description

• Manage model registries, continuous training loops, and A/B testing infra.
• Deploy agents as scalable microservices on Kubernetes.
• Build observability dashboards for token usage, latency, and reasoning paths.

🎯 Requirements

• Strong DevOps/MLOps background (Kubernetes, Docker, Terraform)
• Experience with MLflow, Weights & Biases, or LangSmith
• Knowledge of building scalable microservice architectures