The Agentic Loop
Generative AI Engineer
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Company Description
The Agentic Loop is an AI publication and learning space focused on the frontier of agentic AI for curious learners, builders, and leaders. It translates fast-moving developments in AI agents, models, and tools into clear, practical language without hype or fearmongering. The platform offers a weekly newsletter, daily posts on usable frameworks and tools, and honest analysis of what is and is not working in agentic AI. It also runs hands-on programs, such as the Production GenAI Engineering Program, to help people move from following AI to building it. The Agentic Loop serves students, practitioners, founders, and leaders who want to actively understand and shape the agentic AI shift.
Role Description
As a Generative AI Engineer at The Agentic Loop, you will design, build, and refine agentic AI systems and workflows that can be used in production and shared with a broad technical audience. You will prototype and evaluate models, build tools and reference implementations, and contribute example projects that demonstrate practical applications of generative AI. Day-to-day, you will collaborate with technical and editorial team members to turn complex AI concepts into robust code, reproducible experiments, and clear documentation. You will help maintain and improve internal infrastructure for experimentation, prompt engineering, evaluation, and deployment, while staying current with new models, frameworks, and best practices. This is a full-time, remote role with flexibility to collaborate asynchronously across time zones.
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Qualifications
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- Strong software engineering skills in languages commonly used for AI (for example, Python, TypeScript/JavaScript, or similar), including writing clean, testable, and well-documented code.
- Experience with modern AI/ML tooling such as deep learning frameworks (e.g., PyTorch, TensorFlow), model APIs (e.g., OpenAI, Anthropic, open-source LLMs), and agentic or orchestration frameworks.
- Background in designing, evaluating, and iterating on generative AI systems, including prompt engineering, retrieval-augmented generation, and building multi-step agent workflows.
- Familiarity with software architecture and DevOps practices relevant to AI applications, such as version control (Git), basic CI/CD, containerization, and cloud platforms.
- Ability to communicate technical concepts clearly through documentation, example projects, and collaboration with editorial and learning program teams.
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
- Experience building educational tools, open-source projects, or developer-focused content is a plus.
- Comfort working independently in a remote environment, taking ownership of projects from idea to production-ready artifacts.
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