Applied AI Engineer

• Commercial experience building and shipping production LLM applications
• Experience designing and implementing AI evaluation frameworks
• Practical experience with LLM-as-a-Judge, golden datasets, or regression testing approaches
• Experience building agentic AI workflows and tool-using agents
• Strong software engineering fundamentals and backend development experience
• Experience with Python and/or TypeScript
• Experience designing APIs and scalable backend services
• Knowledge of prompt engineering and prompt lifecycle management
• Understanding of defensive engineering patterns such as rate limiting, idempotency, and backoff strategies

Nice to have:

• Experience with LangChain or similar orchestration frameworks
• Experience with Retrieval-Augmented Generation (RAG)
• Experience with vector databases and semantic search
• Experience with Vision-Language Models (VLMs)
• Experience building multimodal AI systems
• Experience creating automated evaluation dashboards and monitoring solutions

• Design, develop, and deploy AI-powered product features using LLMs and multimodal models
• Build and maintain backend services supporting AI applications and workflows
• Develop evaluation frameworks, golden datasets, and automated quality measurement pipelines
• Design and implement multi-step agent workflows with tool usage, memory, error recovery, and human-in-the-loop processes
• Build scalable APIs and backend components supporting AI services
• Improve model reliability, performance, and response quality in production environments
• Implement engineering best practices including testing, monitoring, rate limiting, retry mechanisms, and fault tolerance
• Collaborate with cross-functional teams to deliver end-to-end AI solutions