Lead Gen AI (Snowflake Cortex)

Job Description: Lead Data Scientist ai Generative AI (Snowflake Cortex Platform)
Job Title: Lead Data Scientist ai GenAI & Intelligent Applications
Experience Level: 8-12 Years
Location: Hybrid
Department: AI, Data Science & Advanced Analytics

Role Overview
As a Lead Data Scientist / GenAI Expert, you will architect and scale our next-generation enterprise AI capabilities natively inside the Data Cloud. Leveraging Snowflake Cortex AI, you will bridge the gap between heavy enterprise data assets and cutting-edge GenAI applications, including multi-modal systems, automated text-to-SQL data interfaces, and autonomous AI agents.
This is a senior technical leadership role requiring deep expertise in Large Language Models (LLMs), vector databases, and orchestration frameworks. You will lead the migration from complex, decoupled AI infrastructure to secure, low-latency, and cost-effective Snowflake-native AI architectures.

Key Responsibilities -

• Cortex Solution Architecture: Design, develop, and operationalize enterprise GenAI solutions utilizing Snowflake Cortex AI tools (such as Cortex Analyst, Cortex Search, and Cortex Agents).
• LLM Pipeline Engineering: Build and optimize framework-agnostic LLM pipelines, prompt engineering pipelines, and complex Retrieval-Augmented Generation (RAG) frameworks using custom enterprise datasets.
• Agentic AI Development: Champion the design of autonomous Agentic AI systems capable of semantic reasoning, tool calling, and workflow execution directly against structured and unstructured enterprise data.
• Model Fine-Tuning & Evaluation: Evaluate, fine-tune, and deploy state-of-the-art open and closed foundation models (e.g., Llama, Mistral, Anthropic).
• Semantic Modeling: Standardize semantic views, metrics, and relationships to empower Cortex Analyst to seamlessly convert natural language business questions into precise, high-performing SQL.
• Data Native DevSecOps: Integrate GenAI solutions with data-engineering orchestration platforms like dbt and Apache Airflow using the Cortex Code CLI workflow.
• AI Governance & Compliance: Enforce enterprise-grade security and role-based access control (RBAC), ensuring that LLMs strictly inherit the native data governance policy configurations of the warehouse.
• Technical Mentorship: Drive the internal engineering community forward by conducting code reviews, setting LLM performance benchmarks, and mentoring mid-to-senior data scientists.

Required Technical Skills & Experience-

• Overall Experience: 8-12 years of professional experience in Data Science, Machine Learning, or NLP, with at least 3+ years completely focused on deploying production GenAI systems.
• Snowflake Core Expertise: Deep practical familiarity with Snowpark (Python/Scala), Snowsight UI, and Snowflake database internals.
• Snowflake Cortex Skills: Hands-on experience executing Snowflake Cortex SQL/Python functions (COMPLETE, SIMILARITY, EMBED_TEXT) and designing end-to-end applications with Cortex Search or Analyst.
• GenAI Orchestration: Fluency with frameworks like LangChain, LlamaIndex, or LangGraph for building multi-turn conversational agents.
• Vector Infrastructure: Proven track record utilizing native Snowflake VECTOR data types, embeddings, and similarity metrics.
• Core Languages: Mastery of Python and advanced data architecture SQL.
• Cloud Architecture: Familiarity with deploying underlying cloud ecosystems (AWS, GCP, or Azure) that anchor modern data lakehouses.

Soft Skills & Leadership Qualities-

• Translational Leadership: Exceptional ability to distill abstract business requirements into highly accurate prompt blueprints and vector schemas.
• First-Principles Engineering: Passionate about minimizing latency, managing token cost variations, and optimizing context windows across varying model dimensions.
• Cross-Functional Collaboration: Ability to work dynamically across the Data Platform, MLOps, and specific Business Units to validate true product-market fit.

Education & Qualifications-

• Bachelors, Masters, or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Computational Linguistics, or an equivalent quantitative STEM discipline.