Onsite AI Architect: GenAI, LLM Deployment & Security

System Soft Technologies; Montgomery (AL); On-site; USD 80,000 - 120,000; Full time

Job summary

System Soft Technologies in Montgomery, Alabama, seeks an onsite AI Application Developer focused on generative and agentic AI. You will build, test, and maintain agentic tools in Python, help design system architecture, and support MCP server integration for AI applications in production.

The role involves deploying and maintaining AI software in Docker containers, assisting with LLMs using vLLM, updating WebUI configurations, creating training materials, and ensuring security compliance with

Qualifications

• Develop, maintain, and test agentic tools using Python as the primary programming language.
• Assist with development of system architecture.
• Build and maintain MCP (Model Context Protocol) servers for AI application integration.
• Deploy, operate, and maintain AI applications in production environments (Docker containers).
• Assist with deployment and maintenance of Large Language Models (LLMs) using vLLM in Docker containerized environments.
• Assist with the maintenance and upkeep of Open WebUI instances and configurations.
• Create documentation and training materials for user education in AI applications.
• Participate in agile development processes and team collaboration.

Responsibilities

• AI Application Development and Testing.
• Develop, maintain, and test agentic tools using Python as the primary language.
• Assist with deployment and maintenance of LLMs using vLLM in Docker environments.
• Deploy, operate, and maintain AI applications in production environments.

Skills

Python

Agile development

Docker

Tools

Git

Azure DevOps

vLLM

Open WebUI

Job description

System Soft Technologies in Montgomery, Alabama, seeks an onsite AI Application Developer focused on generative and agentic AI. You will build, test, and maintain agentic tools in Python, help design system architecture, and support MCP server integration for AI applications in production.

The role involves deploying and maintaining AI software in Docker containers, assisting with LLMs using vLLM, updating WebUI configurations, creating training materials, and ensuring security compliance with