UsefulBI Corporation - Generative AI Architect

Role Overview :

We are looking for a GenAI Engineer with hands-on experience in building LLM-powered applications, especially Retrieval-Augmented Generation (RAG) systems. The ideal candidate should be comfortable working with structured and unstructured data, embeddings, vector databases, and deploying GenAI solutions in real-world environments.

Key Responsibilities :

- Design and build RAG-based GenAI applications

- Work with structured (DBs, tables) and unstructured data (PDFs, docs, text)

- Implement document ingestion, chunking, embedding generation, and retrieval

- Integrate LLMs (OpenAI, Azure OpenAI, open-source models like LLaMA/Mistral)

- Use vector databases for similarity search and retrieval

- Optimize prompts, context size, and response quality

- Build APIs/services to expose GenAI functionality

- Collaborate with backend, data, and DevOps teams

- Handle evaluation, logging, and basic monitoring of GenAI outputs.

Required Skills (Must Have) :

- Strong understanding of LLMs and GenAI fundamentals

- Hands-on experience with RAG architecture

- Experience handling :

1. Structured data (SQL / NoSQL)

2. Unstructured data (PDFs, text, documents)

3. Embeddings and similarity search concepts

- Vector databases (any one) :

1. FAISS

2. ChromaDB

3. Pinecone

4. Weaviate

- Python for GenAI pipelines(Must have)

- Prompt engineering basics

- API integration experience