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Company Description The Agentic Loop is an AI-focused publication dedicated to helping curious individuals, builders, and leaders make sense of the rapid shift toward agentic AI. The team covers the frontier of AI agents, the models powering them, and the people creating them, with a clear focus on what these developments mean in practice. By translating complex, hype-filled, and jargon-heavy conversations into straightforward insights, The Agentic Loop offers practical, signal-driven perspectives on what is working and what is not. Offerings include a weekly newsletter on major moves in agentic AI, daily posts on usable tools and frameworks, and in-depth conversations with leading practitioners. The publication is designed for anyone who wants to actively understand and engage with the agent age rather than passively observe it.
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 iterate on agentic AI systems and tools that support content creation, research workflows, and audience-facing products. Day-to-day responsibilities include prototyping and evaluating LLM-based agents, integrating external APIs and data sources, and fine-tuning or configuring models to improve reliability, safety, and usability. The role involves close collaboration with editorial and product teams to translate emerging AI capabilities into practical features for readers and subscribers. The engineer will also monitor performance, run experiments, document architectures and best practices, and contribute to internal frameworks that make agentic AI easier to build, test, and understand.
Qualifications
- Strong proficiency in software engineering fundamentals (e.g., Python or similar languages, version control, testing, and debugging) and experience building production-ready applications or tools.
- Hands-on experience with large language models and generative AI (e.g., prompt engineering, agent design, orchestration frameworks, fine-tuning or model configuration, and evaluation of model outputs).
- Familiarity with AI and data tooling (e.g., cloud platforms, vector databases, embeddings, model APIs, and integration with external data or services).
- Ability to design and implement robust, user-centered systems (e.g., workflow automation, reliability and safety mechanisms, logging and monitoring, and iterative improvement based on feedback).
- Comfort working cross-functionally with editorial, product, and design teams, with strong communication skills and an ability to translate technical concepts into clear, practical language.
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience in AI, machine learning, or software development.
- Curiosity about the future of agentic AI, a habit of staying current with frontier models and tools, and an interest in building systems that help others understand and use AI
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