Lead AI Engineer
Core
Deploy, configure, and manage AI models, agentic systems, and supporting infrastructure in cloud and on-premise environments.
Role type
Lead MLOps/Agent Ops Engineer
Builds
Production AI/ML models and agentic applications
Domain
Cloud infrastructure and AI/ML operations
Deliverable
production ML models
Required skills
Cloud platform management (GCP), CI/CD pipeline implementation, Infrastructure as Code (Terraform, Ansible), Container orchestration (Kubernetes), Monitoring and logging (Prometheus, Grafana, Datadog), Scripting (Python, Bash), Incident response and root cause analysis, Automation tooling
Preferred skills
Agentic AI concepts, Vector database management, Data pipeline tools (Airflow, Kubeflow), AI/ML frameworks (TensorFlow, Pytorch)
Technologies
Google Cloud Platform, Vertex AI, Docker, Kubernetes, Terraform, Ansible, Prometheus, Grafana, ELK Stack, Datadog, Langfuse, Python, Bash, PowerShell, Bitbucket, GitLab CI, GitHub Actions, Apache Airflow, Kubeflow Pipelines
Responsibilities
Deploy and manage AI models and agentic systems in cloud/on-premise environments, Implement and maintain CI/CD pipelines for AI/ML models, Develop monitoring, logging, and alerting solutions for AI agents, Provide operational support including incident response and troubleshooting, Automate routine operational tasks and deployment processes, Collaborate with AI developers and architects to ensure smooth production transitions
Seniority
Senior, hands-on IC
