Job Summary :

We are looking for a skilled Senior AI Engineer with 4-9 years of experience in GenAI core skills including RAG pipelines, Langchain, Agentic AI frameworks, Python, FastAPI, and Azure AI services.

What you will do :

- Design, develop, and deploy scalable GenAI solutions using LLMs, RAG architectures, and Azure cloud.

- Lead the development and implementation of LLM- and RAG-based applications, ensuring adherence to ML and DL best practices.

- Build and maintain AI pipelines including data cleaning, pre-processing, feature engineering, training, validation, and inference.

- Design and optimize Retrieval-Augmented Generation (RAG) workflows using vector databases (e.g., FAISS, Azure AI Search, Weaviate).

- Deploy GenAI solutions using Azure OpenAI, Blob Storage, Cosmos DB, Key Vault, and Azure Container Apps.

- Evaluate model performance and factuality using RAGAS, and apply iterative improvements.

- Use orchestration frameworks such as LangChain, LangGraph, or AutoGen for scalable and modular GenAI workflows.

- Collaborate with DevOps and infrastructure teams for deployment, monitoring, and logging of AI systems.

- Conduct code reviews, mentor junior developers, and promote clean, maintainable code.

- Document AI architecture, pipelines, and decisions to support transparency and knowledge sharing.

Tech Stack :

Python, Transformers, Azure OpenAI, Weaviate/Azure AI Search, RAGAS, LangChain, Cosmos DB, FastAPI, containerization, and prompt engineering.

Requirements :

- 2+ years of experience in GenAI core skills (RAG, Langchain, Agentic AI).

- 3-5 years of experience in Python.

- 2-3 years of experience in API creation using FastAPI.

- 1-2 years of experience in Azure AI services.