We are seeking an experienced AI Engineer with hands-on expertise in Retrieval-Augmented Generation (RAG) to design, build, and deploy AI solutions powered by Large Language Models (LLMs). The role focuses on integrating LLMs with enterprise data sources to deliver accurate, secure, and scalable AI applications.

Key Responsibilities

Design and implement RAG pipelines using structured and unstructured data

Develop and optimize LLM-based applications (chatbots, copilots, internal tools)

Build document ingestion, embedding, and vector search workflows

Integrate vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma)

Implement prompt engineering, query optimization, and response evaluation

Deploy and monitor AI solutions in production environments

Collaborate with product, backend, and business teams

Ensure data security, access control, and compliance in AI systems

Requirements

Bachelor’s degree in Computer Science, AI, or related field

3–5 years of experience in AI / Machine Learning

Proven hands-on experience with RAG architectures

Strong proficiency in Python

Experience with LLM frameworks such as LangChain, LlamaIndex, or Haystack

Solid understanding of embeddings, similarity search, and vector indexing

Experience working with APIs (OpenAI, Azure OpenAI, open-source LLMs)

Good knowledge of SQL and data preprocessing techniques

Please send your resume/CV