DevOps Engineer

Role Summary

Deploy, automate, secure and maintain the university's AI/ML, Generative AI and Moodle/CULMS platforms across AWS, on-premise and hybrid environments, from model serving and RAG to CI/CD, LMS upgrades and production reliability.

Key Responsibilities

• Build CI/CD pipelines for AI, RAG, API and LMS applications, with automated testing, Docker builds, security checks and rollback; manage GitOps and IaC (Terraform/Ansible/Helm).
• Deploy and optimize LLMs (Llama, Qwen, Mistral, Gemma) via vLLM, Ollama or Hugging Face on AWS/on-premise GPUs, managing CUDA environments, performance and cost.
• Deploy RAG pipelines and vector databases (Qdrant, Milvus, Weaviate, pgvector) along with Python/FastAPI AI services.
• Manage AWS (EC2/GPU, EKS, ECR, S3, VPC, IAM, CloudWatch), hybrid connectivity, backup, recovery, scaling and cost optimization.
• Containerize services with Docker and run them on Kubernetes/EKS, including ingress, secrets, storage, scaling and troubleshooting.
• Own Moodle/CULMS deployments, upgrades, patches and the plugin lifecycle (compatibility, security, UAT, release), plus cron, caching, backups and CUIMS/ERP, SSO and LTI integrations.
• Monitor platforms with Prometheus, Grafana and CloudWatch; handle incidents, root-cause analysis and disaster recovery.
• Enforce security (IAM, secrets, TLS, least privilege, patching), protect institutional data and maintain change documentation.

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