Beschreibung
Please make sure to include your CV incl. AI competency description and Agentic AI project references!
We are looking for a highly skilled freelancer to implement intelligent, autonomous agents within a multi-agent AI system tailored for expert sourcing workflows.
This role is focused on the hands-on development of intelligent agent behavior in a hierarchical AI system designed to automate and streamline expert sourcing. You will be implementing core agent logic, particularly for the Supervisor Agent and its sub-agents, so they can autonomously handle complex tasks such as candidate evaluation, task routing, and process coordination.
Your work will bring to life dynamic task decomposition, reasoning capabilities, memory handling, and inter-agent communication. You will also be responsible for ensuring robust integration with system components such as message buses, task queues, APIs, and databases. This is a deeply technical role requiring experience with distributed agent systems, prompt engineering, and AI frameworks.
You’ll be part of a team and work closely with others. Clear communication is key, as tasks are coordinated and prioritized together. Active collaboration is essential.
Required Skills/Tools Experience:
- Languages & Frameworks/Tools: TypeScript (NestJS), Python (FastAPI or Flask), Docker, NX
- Agentic AI Tools: mastra, LangChain, AutoGPT, CrewAI (or similar)
- Task & Message Infrastructure: NATS, Celery, Kafka
- Databases: PostgreSQL, pgvector
- API Design: REST, GraphQL, Webhooks, MCP, Websocket
- Agent Concepts: Reasoning, prompt engineering, agent memory, task planning
- Architecture Style: Non-blocking, event-driven systems
- Other: Familiarity with distributed systems, agent execution environments, API interaction
Main task/activity
Design, develop, and integrate intelligent AI agents with capabilities for decision-making, planning, task routing, lifecycle management, and robust communication with system infrastructure, ensuring reliability, memory, and knowledge integration across backend systems.
Other tasks and activities
- Implement the decision-making and reasoning logic for the Supervisor Agent and specialized sub-agents
- Develop task decomposition, agent memory, and planning functionalities
- Integrate agent behavior with message bus systems and task queues
- Build agent workflows for dynamic task routing and delegation
- Handle agent lifecycle management, including initialization, execution, and termination
- Ensure robust response validation, error handling, and logging
- Connect agents to databases for knowledge storage and retrieval
- Collaborate with backend and system integration layers for seamless execution
Please provide ENGLISH documents only
We are looking for a highly skilled freelancer to implement intelligent, autonomous agents within a multi-agent AI system tailored for expert sourcing workflows.
This role is focused on the hands-on development of intelligent agent behavior in a hierarchical AI system designed to automate and streamline expert sourcing. You will be implementing core agent logic, particularly for the Supervisor Agent and its sub-agents, so they can autonomously handle complex tasks such as candidate evaluation, task routing, and process coordination.
Your work will bring to life dynamic task decomposition, reasoning capabilities, memory handling, and inter-agent communication. You will also be responsible for ensuring robust integration with system components such as message buses, task queues, APIs, and databases. This is a deeply technical role requiring experience with distributed agent systems, prompt engineering, and AI frameworks.
You’ll be part of a team and work closely with others. Clear communication is key, as tasks are coordinated and prioritized together. Active collaboration is essential.
Required Skills/Tools Experience:
- Languages & Frameworks/Tools: TypeScript (NestJS), Python (FastAPI or Flask), Docker, NX
- Agentic AI Tools: mastra, LangChain, AutoGPT, CrewAI (or similar)
- Task & Message Infrastructure: NATS, Celery, Kafka
- Databases: PostgreSQL, pgvector
- API Design: REST, GraphQL, Webhooks, MCP, Websocket
- Agent Concepts: Reasoning, prompt engineering, agent memory, task planning
- Architecture Style: Non-blocking, event-driven systems
- Other: Familiarity with distributed systems, agent execution environments, API interaction
Main task/activity
Design, develop, and integrate intelligent AI agents with capabilities for decision-making, planning, task routing, lifecycle management, and robust communication with system infrastructure, ensuring reliability, memory, and knowledge integration across backend systems.
Other tasks and activities
- Implement the decision-making and reasoning logic for the Supervisor Agent and specialized sub-agents
- Develop task decomposition, agent memory, and planning functionalities
- Integrate agent behavior with message bus systems and task queues
- Build agent workflows for dynamic task routing and delegation
- Handle agent lifecycle management, including initialization, execution, and termination
- Ensure robust response validation, error handling, and logging
- Connect agents to databases for knowledge storage and retrieval
- Collaborate with backend and system integration layers for seamless execution
Please provide ENGLISH documents only