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