What are the responsibilities and job description for the AI Engineer-Snowflake position at Virtual Labs?
Position: Sr AI Engineer with Snowflake
Location: Plainsboro NJ ( 4 days Office)
Description:
Core Responsibilities
- 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.
- Domain Alignment: Apply data science methodologies to solve specific problems in Pharma Commercial and Sales (e.g., patient longitudinal data, HCP targeting, and marketing ROI).
Technical Requirements
- 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.