1. Position
We are seeking mid-Level AI application & Cloud operations engineer to support the operation, stability, performance, and security of enterprise AI applications running on Samsung Cloud Platform and AWS Bedrock. The engineer will support AI services including Claude Chat, HE T2A, and Cowork for SEA, with a focus on Linux systems, Python-based applications, Docker, databases, networking, AWS services, and production troubleshooting
2. Core responsibilities.
• 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 Samsung 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.
3. Qualification
• 5–9 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/Node.js 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.
4. 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 PrometheGrafana or ELK Stack.
• AWS certification such as Solutions Architect, SysOps Administrator, or DevOps Engineer.
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