Full Stack AI Solution Developer

Position would require the candidate to be a W2 employee of Donatech. US Citizenship Required.

• Development of AI-enabled solutions from prototype/proof-of-concept maturity into operational capability.

• Develop, maintain, and troubleshoot frontend applications and backend services.

• Support development and sustainment of Model Context Protocol (MCP) services.

• Support integration of AI/LLM capabilities, agent workflows, and model/tool interactions into enterprise applications.

• Design and implement database and data engineering capabilities, including selection of appropriate database technologies, schema/data model design, data access patterns, and integration with application services.

• Develop and maintain containerized applications using Docker and deploy solutions to OpenShift/Kubernetes environments.

• Build and maintain GitLab repositories, branching strategies, merge request practices, and GitLab CI/CD pipelines that automate build, test, containerization, and deployment activities.

• Automate deployment to OpenShift using Helm charts and related deployment/configuration management practices.

• Integrate applications with enterprise authentication and authorization patterns

• Identify and troubleshoot application, container, deployment, integration, authentication, database, and performance issues across the full stack.

• Develop and maintain technical documentation, operational procedures, troubleshooting guides, and sustainment handoff materials.

Basic Qualifications:

• 5+ years of experience performing full stack software development.

• Hands-on experience developing and sustaining frontend and backend services.

• Experience using GitLab for source control, code review, merge requests, and team-based software development.

• Experience deploying, operating, or troubleshooting applications in OpenShift or Kubernetes environments.

• Experience with modern software delivery practices, including automated build, test, packaging, containerization, and deployment.

• Experience with data engineering concepts, data modeling, data persistence, and application/database integration.

• Knowledge of OAuth 2.0 or similar authentication and authorization patterns.

• Ability to review and understand code developed by others, including AI-assisted code, and determine whether it is correct, maintainable, secure, and operationally supportable.

Desired Skills:

• Experience with observability, logging, monitoring, and troubleshooting tools.

• Familiarity with ServiceNow or similar IT service management platforms.

• Experience developing, integrating, or sustaining AI-enabled applications, LLM-based solutions, agentic workflows, or AI-assisted automation capabilities.

• Familiarity with LangGraph or similar Python-based agentic frameworks.

• Familiarity with Model Context Protocol (MCP), tool calling, skills, agents, prompts, context windows, token usage, and LLM application design considerations.

• Highly adaptive to priority changes, able to work independently, and able to balance rapid development with long-term maintainability and sustainment.

• Familiarity with AI/ML infrastructure, responsible AI considerations, and practical limitations of LLM-based systems.