iCapital

DevOps Engineer

• Design, build, and operate MLOps pipelines supporting the full ML lifecycle (training, validation, deployment, monitoring)
• Enable production workloads for AI/ML and Generative AI systems, including LLM‑based services
• Develop and maintain CI/CD pipelines for AI/ML services and supporting infrastructure
• Build and manage cloud‑native infrastructure on AWS, with heavy use of Kubernetes and containerized workloads
• Automate infrastructure provisioning and configuration using Infrastructure as Code (Terraform)
• Implement model versioning, experiment tracking, and artifact management across environments
• Ensure reliability, scalability, observability, and cost efficiency of AI platforms
• Partner with AI/ML engineers to operationalize models and standardize deployment patterns
• Implement monitoring and alerting for system health, model performance, and drift
• Enforce security, compliance, and governance requirements for AI workloads
• Participate in incident response, root cause analysis, and continuous improvement initiatives
• Document standards, best practices, and reference architectures for MLOps and AI infrastructure.

Senior DevOps Engineer