Generative AI Engineer

Company Description

The Agentic Loop is an AI publication and learning space focused on agentic AI, serving curious learners, builders, and leaders. It translates fast-moving developments in AI into clear, practical language, cutting through hype and jargon to provide actionable insight. The platform offers a weekly newsletter, daily posts on news, frameworks, and tools, and honest analysis of what is and isn't working in the field. It also runs hands-on programs, such as the Production GenAI Engineering Program, to help people move from following AI to building real systems. The Agentic Loop is designed for anyone who wants to understand and actively shape the emerging agent age.

Role Description

The Generative AI Engineer will design, build, and iterate on agentic AI systems that support The Agentic Loop's educational content, tools, and programs. In this full-time remote role, the engineer will develop and evaluate prompts, fine-tune and integrate models, and create reliable pipelines for data ingestion, transformation, and evaluation. Day-to-day responsibilities include prototyping new agent workflows, implementing APIs and backend services, experimenting with model configurations, and improving system performance and safety. The engineer will collaborate closely with content creators and program leads to turn frontier developments into practical, usable tools for learners and practitioners. The role also involves monitoring models in production, documenting architectures and best practices, and contributing to internal frameworks for agentic AI.

Qualifications

• Strong skills in software engineering and backend development (e.g., Python, REST APIs, microservices, integration with external APIs).
• Experience with modern machine learning and generative AI tooling (e.g., LLMs, embeddings, vector databases, orchestration frameworks such as LangChain or equivalent).
• Knowledge of data engineering and evaluation practices (e.g., data pipelines, dataset curation, automated evaluation, logging and monitoring of AI systems).
• Ability to design, test, and refine prompts, agents, and workflows for real-world use cases, with attention to reliability and safety.
• Comfort working in a fast-moving environment, learning new tools quickly, and communicating complex technical concepts in clear language.
• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• Prior experience building production-grade AI or ML systems is strongly preferred; experience in education, media, or developer tooling is a plus.