AI Application & Cloud Operations Engineer (Mid level)

Sbtglobalinc; Plano (TX); On-site; USD 90,000 - 135,000; Full time

Job summary

Sbtglobalinc is seeking a skilled DevOps/Platform Engineer to operate and monitor enterprise AI applications in a Linux-based production environment. You will manage Docker, NGINX, and Python services, while ensuring robust CI/CD and incident response capabilities.

The role requires 5-9 years of hands-on experience with Linux systems, cloud services, databases, and AI application components. A strong scripting background and familiarity with Kubernetes is highly valued.

Qualifications

• 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.

Responsibilities

• Operate and monitor enterprise AI applications and services.
• Manage Linux servers, Docker containers, NGINX, and systemd services in production.
• 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).
• Maintain technical documentation and operational procedures.

Skills

Linux administration

Python scripting

Bash scripting

REST APIs

Troubleshooting

Tools

Docker

NGINX

Uvicorn

Gunicorn

PostgreSQL

MongoDB

Redis

Meilisearch

Kubernetes

Job description

• 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.

• 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.

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.

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