We are seeking an experienced AI Engineer specializing in multi-agent LLM systems. This role requires a deep understanding of constructing, training, and deploying AI agents that can dynamically execute Python-based functions in response to specified needs. As part of our team, you’ll develop agents that can autonomously select and perform functions based on contextual requirements and work seamlessly within a robust AWS infrastructure.

Responsibilities:

• Design, implement, and deploy AI agents that can autonomously learn to select and execute custom functions using Python.
• Train agents to recognize contextual prompts and determine the necessary function to perform specific tasks, optimizing for accuracy and efficiency.
• Develop frameworks for dynamic task assignment within multi-agent systems, enabling agents to coordinate and collaborate effectively on complex workflows.
• Deploy and manage the multi-agent system within the AWS environment (e.g., Lambda, SageMaker, EC2), ensuring scalability and resilience.
• Work closely with cross-functional teams to define function requirements and develop APIs or connectors for seamless task execution.
• Implement strategies to improve model performance in function execution, covering error handling, retry mechanisms, and adaptability to changing requirements.
• Document designs, workflows, and function-specific agent behaviors to support team collaboration and product transparency.

Requirements

• Proven Experience: 1+ years working with LLMs, with a strong focus on developing function-driven multi-agent systems.
• Technical Skills: Expertise in Python and experience with custom function execution within LLM frameworks; skilled in prompt engineering, model fine-tuning, and dynamic function mapping. Experience in OpenAI Swarm and other relevant tech is a plus.
• AWS Expertise: Demonstrated ability to deploy and manage models within AWS, using Lambda, SageMaker, EC2, and other essential AWS tools.
• Web3 Knowledge: Familiarity with blockchain principles and web3 technologies is a plus.
• Problem-Solving Skills: Experience developing autonomous, adaptable agents capable of selecting and performing tasks based on contextual cues.
• Communication: Strong documentation skills for cross-functional alignment and clear communication of complex workflows.

Preferred Qualifications:

• Experience with reinforcement learning or decision-making models to enhance autonomous task selection.
• Familiarity with Docker and Kubernetes for robust, containerized deployments.
• Previous experience in web3 or blockchain environments, including working with smart contracts or decentralized applications.

Benefits

• HMO
• Work From Home
• Tokens
• Leave Credits
• Training & Development