Builds backend platform for multi-agent AI systems, integrating multiple LLMs and orchestration frameworks like LangGraph. Requires deep expertise in AI/ML, agent workflows, evaluation, privacy, and search integration.
200k – 250k/yr
RemoteML Engineering
About the role
Key Responsibilities
Design, develop, and maintain a robust platform to enable users to create and manage AI agents and their interactions.
Integrate and work with multiple LLMs, ensuring seamless orchestration and scalability for both individual and coordinated agent operations.
Leverage orchestration frameworks like LangGraph and others to build complex workflows and pipelines that support diverse agent functionalities, including frameworks for multi-agent coordination.
Develop and implement evaluation frameworks for testing AI agents in challenging and complex scenarios, focusing on individual performance and system-level dynamics.
Stay at the forefront of AI advancements, incorporating the latest research and technologies into our platform to enhance agent capabilities and collaboration.
Collaborate with cross-functional teams, including product managers, designers, and frontend engineers, to deliver a seamless user experience for building and deploying intelligent systems.
Address challenging AI privacy scenarios, ensuring compliance with data protection regulations and best practices within agent-based applications.
Contribute to improving search capabilities and integrating them into the AI platform to provide agents with essential information access.
Qualifications
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.
Passion for staying updated with the latest developments in AI and applying them to real-world problems, particularly in the realm of agent technologies.
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.
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