Generative AI Engineer

Company Description The Agentic Loop is an AI publication and learning space focused on the frontier of agentic AI, spotlighting real-world agents, the models powering them, and the people building them. It translates complex and fast-moving AI developments into clear, practical language for a broad audience, avoiding hype and fearmongering. The platform offers a weekly newsletter, daily posts, and honest analysis of what is working in agentic AI and what is not. It also hosts hands-on programs, such as the Production GenAI Engineering Program, to help people move from following AI to building it themselves. The Agentic Loop serves students, builders, founders, leaders, and anyone curious about the future of AI. Role Description This is a full-time remote role for a Generative AI Engineer at The Agentic Loop. The Generative AI Engineer will design, build, and evaluate agentic and generative AI systems, including workflows that integrate large language models, tools, and APIs. Day-to-day work includes prototyping new agents, experimenting with model configurations, prompt engineering, and optimizing performance, reliability, and safety. The role also involves collaborating with content and program leads to turn frontier research and engineering best practices into practical examples, demos, and educational materials. The engineer will document architectures, write clear technical explanations, contribute to internal tools and libraries, and help shape the platform’s view on production-grade generative AI. Qualifications Strong programming skills in languages commonly used for AI engineering (e.g., Python, JavaScript/TypeScript) and familiarity with software development best practices (testing, version control, CI/CD). Experience working with modern generative and agentic AI frameworks (e.g., LLM APIs, orchestration frameworks, vector databases, tool-using agents) and building end-to-end prototypes. Solid understanding of machine learning and deep learning fundamentals, including model evaluation, prompt design, and techniques for improving reliability, safety, and robustness. Ability to translate complex technical concepts into clear, practical explanations, examples, and documentation for both technical and non-technical audiences. Comfort working in a remote, fast-moving environment with strong ownership, curiosity, and a bias toward experimentation and learning. Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field, or equivalent practical experience in AI engineering. Experience deploying AI-powered applications in production environments and familiarity with cloud platforms or modern infrastructure tools is beneficial. Interest in agentic AI, emerging tools and frameworks, and a commitment to responsible, non-hype-driven communication about AI. Show more Show less