Artificial Intelligence Engineer

We're looking for AI Engineers who have built complex, production LLM-based systems. Whether you've scaled LLM workflows handling millions of requests, built multi-agent systems in production, or designed evaluation frameworks for enterprise deployments, we want people who bring intensity and self-direction to their craft. You'll spend most of your time advancing our core learning library and building the harness that powers our platform's agents across all customers. The work spans continuous learning systems, agentic features, human-in-the-loop feedback loops, and agent orchestration. Build and extend our core context-learning library, turning customer-informed problems into reusable platform capabilities. Design and implement LLM-powered systems and agentic workflows from concept to production Build agentic features for knowledge management-think agents that can edit, update, and maintain large knowledge bases autonomously Build reliability and confidence systems-evaluation frameworks, confidence scoring, and logic for when to automate vs. when to escalate to a human Architect async, scalable systems that handle complex AI orchestration Contribute to the direction of our AI strategy and product capabilities Previous Experience You've built complex, production LLM-based systems with real depth-something with multiple layers of engineering decisions you can walk through in detail You've shipped something meaningful to production and can explain how it evolved You're excited by open-ended problems where the solution might not exist yet You have experience with (or strong interest in) how systems learn and improve over time: human-in-the-loop feedback, prompt optimization and context engineering You have experience building agents and autonomous systems You can navigate between research papers and production code with equal comfort You're a strong communicator who can clearly explain your work to teammates and customers Show more Show less