AI Application & Cloud Operations Engineer (Mid level)

      Operate and monitor enterprise AI applications including Claude Chat HE T2A and Cowork for SEA.

      Manage Linux servers Docker containers NGINX and systemd services in production environments.

      Support and troubleshoot Python-based applications and APIs using Flask FastAPI Uvicorn and Gunicorn.

      Manage and monitor MongoDB PostgreSQL/pgvector Redis and Meilisearch.

      Support integration with AWS Bedrock (Claude) and external AI services such as Tavily API.

      Manage company Cloud Platform VMs running RHEL and Ubuntu.

      Support secure network connectivity using IPsec VPN AWS PrivateLink and VPC Endpoints.

      Monitor system health application performance and audit activities using CloudWatch and CloudTrail.

      Support file storage firewall rules routing MCP Server and Filebridge components.

      Develop Python and Bash automation scripts for deployment monitoring backup and recovery.

      Support CI/CD deployment processes and improve operational efficiency.

      Perform incident response troubleshooting and root-cause analysis (RCA) and implement preventive measures.

      Maintain technical documentation and operational procedures.

Qualifications :

      59 years of experience in application system or cloud operations.

      Strong hands-on experience with Linux (RHEL/Ubuntu) administration and production troubleshooting.

      Proficiency in Python and Bash scripting; JavaScript/ experience is a plus.

      Experience operating Flask/FastAPI applications Docker NGINX Uvicorn or Gunicorn.

      Working knowledge of PostgreSQL and/or MongoDB and related operational tasks.

      Experience with AWS services preferably AWS Bedrock CloudWatch CloudTrail and VPC networking.

      Understanding of REST APIs networking VPN PrivateLink and VPC Endpoints.

      Experience with Git and CI/CD tools such as Jenkins.

      Strong troubleshooting incident management and problem-solving skills.

Preferred Qualifications

      Experience operating LLM/GenAI applications or RAG-based systems.

      Hands-on experience with AWS Bedrock and Claude.

      Experience with Redis pgvector Meilisearch or other AI application data stores.

      Experience with MCP AI agents or AI application frameworks.

      Experience with Kubernetes or container orchestration.

      Experience with Prometheus/Grafana or ELK Stack.

    AWS certification such as Solutions Architect SysOps Administrator or DevOps Engineer.

Additional Information :

All your information will be kept confidential according to EEO guidelines.

Remote Work :

No

Employment Type :

Contract