Snowflake Cortex AI Engineer

Snowflake Cortex AI:

Strong hands-on experience designing and implementing AI solutions using Snowflake Cortex capabilities, including Cortex Analyst, Cortex Search, Cortex Agents, AISQL Functions, and Semantic Models. Ability to build enterprise-grade AI and GenAI use cases leveraging Snowflake-native capabilities.

Generative AI & Large Language Models (LLMs):

Experience developing GenAI solutions using LLMs, prompt engineering, Retrieval-Augmented Generation (RAG), vector embeddings, semantic search, and AI agent architectures to solve complex business challenges.

Snowflake Data Modeling & SQL:

Expertise in SQL development and designing dimensional, analytical, semantic, and business data models to support AI-driven analytics and governed business metrics.

Cortex Search & Knowledge Retrieval:

Experience building enterprise search and document intelligence solutions using Cortex Search, enabling efficient retrieval of structured and unstructured business information.

Cortex Agents & AI Orchestration:

Hands-on experience designing and configuring AI agents that orchestrate workflows across multiple data sources, business applications, and AI services.

Python Development:

Strong programming skills in Python for developing AI applications, data processing workflows, API integrations, and automation solutions within the Snowflake ecosystem.

Streamlit in Snowflake (SiS):

Experience developing interactive AI-powered applications, dashboards, and user interfaces using Streamlit in Snowflake and related frameworks.

Snowflake Governance & Administration:

Knowledge of Snowflake security, RBAC, governance frameworks, monitoring, performance tuning, data access controls, and cost optimization strategies.

AI Solution Architecture:

Ability to design scalable, secure, and high-performing AI architectures integrating enterprise data platforms, business systems, and Snowflake-native AI capabilities.

Stakeholder Management & Business Analysis:

Strong communication and consulting skills with the ability to understand business requirements and translate them into measurable AI-driven business outcomes.

Snowflake Document AI:

Experience implementing document processing, OCR extraction, document classification, and intelligent information extraction using Snowflake Document AI.

Snowpark Python:

Experience building scalable data transformation and machine learning workflows using Snowpark Python.

Snowflake Notebooks:

Knowledge of developing, testing, and documenting AI and data science solutions using Snowflake Notebooks.

Dynamic Tables, Streams & Tasks:

Experience creating automated data pipelines, near-real-time data processing workflows, and event-driven architectures within Snowflake.

Cortex ML & Model Evaluation:

Understanding of Cortex ML capabilities, model observability, evaluation frameworks, vector embeddings, and AI performance monitoring techniques.

dbt (Data Build Tool):

Experience implementing data transformation, data quality, testing, and analytics engineering practices using dbt.

CI/CD & DevOps:

Knowledge of CI/CD pipelines, DevOps practices, source control management, automated deployments, and release management for AI solutions.

Infrastructure as Code (IaC):

Experience provisioning and managing cloud resources using IaC tools such as Terraform or similar automation frameworks.

BI & Enterprise Integrations:

Experience integrating Snowflake AI solutions with Power BI, Tableau, Microsoft Copilot, or other enterprise reporting and collaboration platforms.

Cloud Platforms & Certifications:

Knowledge of Azure, AWS, or GCP cloud services and relevant certifications such as SnowPro, GenAI, Azure AI Engineer, AWS AI/ML, or GCP AI certifications.