AI Engineer (Multi-Agent LLM Systems)

1 Month ago • 1 Years + • DevOps

Job Summary

Job Description

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. Responsibilities include designing, implementing, and deploying AI agents that autonomously learn to select and execute custom Python functions; training agents to recognize contextual prompts and determine necessary functions; developing frameworks for dynamic task assignment within multi-agent systems; deploying and managing the system within AWS (Lambda, SageMaker, EC2); collaborating with cross-functional teams; implementing strategies to improve model performance; and documenting designs and workflows. The ideal candidate will have 1+ years of experience working with LLMs, focusing on function-driven multi-agent systems, and expertise in LangChain/LangFlow/LangGraph. AWS experience, including Lambda, SageMaker, and EC2, is essential.
Must have:
  • 1+ years experience with LLMs and function-driven multi-agent systems
  • Expertise in LangChain/LangFlow/LangGraph
  • Python expertise and custom function execution within LLM frameworks
  • AWS experience (Lambda, SageMaker, EC2)
  • Prompt engineering, model fine-tuning, and dynamic function mapping skills
Good to have:
  • Reinforcement learning or decision-making model experience
  • Docker and Kubernetes experience
  • Web3/blockchain experience
  • OpenAI Swarm experience
Perks:
  • Work From Home
  • Tokens
  • Leave Credits
  • Training & Development

Job Details

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.
  • Experience in using LangChain/LangFlow/LangGraph is required.
  • 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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About The Company

Sovrun is redefining gaming by empowering players to truly own their digital assets and take an active role in shaping their virtual worlds.


Our innovative ecosystem bridges the gap between accessible features like NFTs and token-based ownership to immersive experiences like co-creating fully on-chain games and Autonomous Worlds (AWs). Whether it's crafting unique assets, driving player-led economies, or building on composable and modular platforms, Sovrun is paving the way for a new era of gaming.


Join us in shaping the future of interactive entertainment where players aren’t just participants but architects of their gaming experiences.

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