- About Aarvian

Aarvian is a "Process-First" AI transformation partner. We specialize in moving global Retailers from fragmented data to Agentic Workflows. We don't build "Black Boxes"; we build bespoke AI solutions directly on our clients' native stacks to drive measurable P&L; impact.
- The Role

As an AI Engineer at Aarvian, you will be responsible for the hands-on development of AI agents and LLM-powered applications. Working within a high-caliber squad of Data Engineers and Scientists, you will turn retail business logic into production-ready code using the Azure Databricks Lakehouse.

Key Responsibilities

- Hands-on Agent Development: Build and iterate on multi-agent workflows (using LangChain or CrewAI) that solve specific retail functions like automated stock replenishment or personalized marketing copy generation.
- Lakehouse Integration: Develop and maintain data pipelines using PySpark and Delta Live Tables to feed high-quality data into AI models.
- RAG Implementation: Build and optimize Retrieval-Augmented Generation (RAG) systems using Azure AI Search and Databricks Vector Search to ensure agents have real-time access to retail catalogs.
- Model Deployment: Deploy LLMs and custom models via Databricks Model Serving (Mosaic AI)



and manage the lifecycle using MLflow.
- Client Tech-Stack Alignment: Ensure all code is written to run natively within the client’s Azure workplace, adhering to strict data security and Unity Catalog governance.

Technical Requirements (The "Must-Haves")

- Experience: 3–5 years of professional experience in a Data Science or AI Engineering role.
- Coding: Strong proficiency in Python (clean, modular code) and SQL.
- Big Data: 1 year of hands-on experience with PySpark and Databricks.
- GenAI: Proven experience building at least one LLM-based application (using OpenAI, Llama, or similar) beyond a simple tutorial.
- Cloud: Familiarity with the Azure portal (Blob Storage, Key Vault, Entra ID). What We Look For (The "Aarvian" DNA)
- The "Builder" Mindset: You enjoy the "messy" part of AI—cleaning data, handling edge cases, and making things work in production.
- Rapid Learner: You stay updated on the weekly shifts in the GenAI landscape (new models, new frameworks).
- Retail Curiosity: You are interested in how AI can reduce waste, optimize shelves, and improve customer experience.

📌 Artificial Intelligence Engineer (Bengaluru)
🏢 Aarvian
📍 Bengaluru