AI Engineer (LLM + LangChain + RAG)

Job Description/Requirements

Responbsibilities:

Design and build AI-powered applications using LLMs, LangChain, and RAG techniques.

Implement intelligent workflows that integrate structured and unstructured data sources.

Create conversational agents and retrieval systems using embeddings, vector stores, and APIs.

Collaborate with frontend/backend engineers to bring LLM features into web or mobile applications.

Keep up with the fast-moving world of generative AI and experiment with bleeding-edge tools.

Apply enterprise frameworks like Spring Boot to wrap or scale LLM services.

Requirements:

Strong understanding of how LLMs work and how to fine-tune or chain them using frameworks like LangChain or LLamaIndex.

Experience with Python (preferred), especially in AI/ML development.

Ability to build, test, and deploy LLM features in real-world applications.

Familiarity with RAG pipelines, vector databases (e.g. FAISS, Pinecone), and embedding techniques.

Comfort working with APIs and integrating AI services.

Curiosity, energy, and a strong desire to learn and grow.

Experience with Java and Spring Boot for building enterprise-grade services.

What You’ll Gain

The opportunity to build truly impactful products that reach thousands of students and educators.

Work alongside a passionate and talented team solving real problems.

Access to cutting-edge tools, mentorship, and a culture of experimentation and innovation.

Industries: Computer Software

Function: Others