AI Engineer with Snowflake

Hands-on AI Development: Build and deploy production-ready AI models and Agentic frameworks directly within the Snowflake Data Cloud.

Snowflake AI Expertise: Leverage Snowflake Cortex AI, Document AI, and Snowpark ML to create automated, intelligent data solutions.

Technical Leadership: Act as the “Lead of Leads” for the offshore team. You aren’t just giving directions-you are reviewing code, troubleshooting complex bugs, and ensuring the team understands the why behind the tech.

Strategic Fix Management: Balance the need for quick tactical fixes to keep demanding customers happy with the implementation of robust, long-term technical fixes that ensure system scalability.

Experience: 10-12 years in technical roles, with a heavy emphasis on Data Science and AI engineering.

Snowflake Proficiency: Strong technical understanding of Snowflake’s engine, specifically how to optimize it for AI/ML workloads (Snowpark, Python UDFs, and Streamlit).

AI/ML Depth: Deep understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and building Agentic systems that can execute tasks autonomously.

Data Science Toolkit: Expert-level Python/SQL and experience with frameworks like PyTorch, TensorFlow, or Scikit-learn integrated into cloud environments.

Industry Context: Previous experience handling Pharma, Marketing, or Finance data is essential.