Applied AI Engineer

📋 Description

• Design and build essential components of agentic systems, including memory, context management
• Develop reusable AI infrastructure that enables new workflows to be introduced quickly
• Build comprehensive evaluation frameworks to measure agent performance, identify failure points
• Integrate testing, tracing, debugging, and evaluation into the software engineering lifecycle as
• Develop systems and validation processes that allow agentic workflows to be thoroughly assessed
• Advance the use of large language models (LLMs) in software development by creating sophisticated

🎯 Requirements

• Strong software engineering background, with proven experience independently delivering complex
• Practical experience building and deploying AI or agentic systems that have operated in production
• Demonstrated understanding of real-world AI engineering challenges, including reliability, latency
• Strong knowledge of agent architectures, tool use, structured outputs, context management
• Advanced practical experience with modern LLMs and the ability to build reliable workflows around
• Hands-on experience using coding agents and agentic development workflows as part of everyday