Staff AI Engineer - Multi-agent Frameworks

ClickUp ClickUp · Enterprise · United States · Engineering

Staff AI Engineer focused on building a platform for creating and deploying intelligent agents with a key focus on collaborative and multi-agentic behaviors, using orchestration frameworks like LangGraph and developing evaluation frameworks for AI agents.

What you'd actually do

  1. Design, develop, and maintain a robust platform to enable users to create and manage AI agents and their interactions.
  2. Integrate and work with multiple LLMs, ensuring seamless orchestration and scalability for both individual and coordinated agent operations.
  3. Leverage orchestration frameworks like LangGraph and others to build complex workflows and pipelines that support diverse agent functionalities, including frameworks for multi-agent coordination.
  4. Develop and implement evaluation frameworks for testing AI agents in challenging and complex scenarios, focusing on individual performance and system-level dynamics.
  5. Stay at the forefront of AI advancements, incorporating the latest research and technologies into our platform to enhance agent capabilities and collaboration.

Skills

Required

  • Proven experience working with multiple LLMs (e.g., OpenAI, Anthropic, Cohere, etc.) and understanding their strengths and limitations.
  • Expertise in orchestration software like LangGraph or similar frameworks used for building and managing agent workflows.
  • Strong background in developing evaluation frameworks for AI systems, particularly in complex testing environments.
  • Deep understanding of AI and machine learning fundamentals, with a focus on backend engineering.
  • Experience with challenging AI privacy scenarios, including data anonymization, secure data handling, and compliance.
  • Experience with search technologies and their integration into AI systems.
  • Experience building or deploying Multi-Agent Frameworks or Multi-Agent Systems.

Nice to have

  • Passion for staying updated with the latest developments in AI and applying them to real-world problems, particularly in the realm of agent technologies.

What the JD emphasized

  • Experience building or deploying Multi-Agent Frameworks or Multi-Agent Systems.

Other signals

  • building a cutting-edge platform that empowers users to create and deploy sophisticated intelligent agents
  • enabling collaborative and multi-agentic behaviors
  • leveraging orchestration frameworks like LangGraph and others to build complex workflows and pipelines that support diverse agent functionalities
  • developing and implementing evaluation frameworks for testing AI agents