Self-Hosted Modular Ai Agent & Automation Platform (Open Source Stack)

Key Objectives:

Deploy an agent-based architecture capable of executing intelligent tasks, responding to users, and managing internal logic and workflows.

Build automated routines using tools like n8n or similar open-source orchestrators, integrating data pipelines, triggers, and external connectors.

Design a lightweight backend infrastructure using PostgreSQL or similar open-source databases for structured storage, logging, and contextual memory.

Connect intelligent agents with internal tools and interfaces, enabling real-time decision-making and automation across departments.

Ensure a fully on-premise setup, with no cloud dependencies, designed to be secure, scalable, and maintainable.

Deliver the project with clear documentation, a logical modular structure, and training if necessary.


Skills Required:

Experience designing and deploying multi-agent systems using open-source LLMs locally (e.g. Qwen, Gemma, DeepSeek).

Strong knowledge of data orchestration tools (e.g. N8n, Node-RED) and workflow logic design.

Solid understanding of relational databases (PostgreSQL, SQLite) and optionally vector DBs for context-aware features.

Familiarity with containerization tools like Docker (Kubernetes is a plus).