In the rapidly evolving world of EdTech, creating interactive and personalized educational content is a formidable challenge. Many existing tools fall short, offering generic solutions that fail to engage students or cater to their unique learning styles. This disconnection leads to a significant drop in student engagement and a gap in effective learning experiences, putting undue pressure on educators to deliver tailored instruction under tight constraints.

At LearnWith.AI, we're transforming the way educational content is created by leveraging AI's potential. Our mission goes beyond developing AI tools; we aim to build sophisticated AI-driven systems that craft dynamic, personalized learning materials. Imagine an AI-powered "Second Brain" for subjects like Science or History—an intelligent repository that generates engaging, adaptive content on a large scale. This pioneering approach not only sets us apart in a competitive market but also redefines the role of AI in education, making learning more accessible, effective, and enjoyable.

This role is not your typical AI engineering position. Rather than focusing solely on coding or abstract AI models, you'll be at the forefront of transforming the educational experience by designing and implementing AI-powered workflows that deliver truly personalized learning. This position is ideal for ambitious innovators who thrive on using advanced technology to drive meaningful, real-world change.

As an integral part of our team, you'll architect AI-driven educational tools with the potential to revolutionize the learning landscape. By utilizing LLMs as domain experts, you'll create contextual knowledge packs and intelligent learning assistants, ensuring our AI-generated content is both impactful and meaningful. If you're passionate about using AI to transform education and are ready to lead projects that challenge the status quo, we want to hear from you.

What You Will Be Doing:

• Crafting AI-Powered Workflows: Seamlessly integrating diverse AI tools, engineering prompts, and refining workflows based on feedback from experts and users.
• Developing Contextual Knowledge Packs: Utilizing LLMs as domain experts to create and manage documents that capture valuable knowledge and insights.
• Designing Data Structures: Implementing data architectures that support business logic with efficiency and scalability.