AI Developer (LLM and Python)

9 Months ago • 1 Years +
Devops

Job Description

This role requires an experienced AI Engineer specializing in multi-agent LLM systems. Responsibilities include designing, implementing, and deploying AI agents that autonomously learn to select and execute custom Python functions. The ideal candidate will train agents to recognize contextual prompts, develop frameworks for dynamic task assignment within multi-agent systems, and deploy and manage the system within AWS (Lambda, SageMaker, EC2). They will also work with cross-functional teams, implement strategies to improve model performance, and document workflows. Experience with LLMs and Python, along with AWS expertise, is crucial. Familiarity with OpenAI Swarm and web3 technologies is a plus.
Good To Have:
  • Reinforcement learning
  • Docker and Kubernetes
  • Web3 experience
  • Smart contract experience
Must Have:
  • 1+ years with LLMs (multi-agent systems)
  • Python expertise, custom function execution
  • AWS (Lambda, SageMaker, EC2)
  • Prompt engineering, model fine-tuning
  • Dynamic function mapping
  • Develop autonomous agents
Perks:
  • HMO
  • Work From Home
  • Tokens
  • Leave Credits
  • Training & Development

Add these skills to join the top 1% applicants for this job

kubernetes
reinforcement-learning
aws
python
docker
smart-contracts
scalability
cross-functional
team-management

Description

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


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