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).Category: IT & ProgrammingSubcategory: Artificial IntelligenceProject size: MediumIs this a project or a position?: ProjectRequired availability: As needed
Keyword: Docker
Price: $500.0
Secondary Price: $1000.0
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