Snowflake Cortex AI Engineer

Project description

We are seeking an experienced Snowflake Cortex AI Engineer to drive the development and deployment of next-generation AI and Generative AI solutions on the Snowflake platform. This role is focused on leveraging the Snowflake Cortex ecosystem to build intelligent business applications, enterprise search solutions, AI-powered analytics, and conversational assistants that enable users to interact with business data through natural language. The ideal candidate will design and implement scalable AI architectures utilizing Cortex Analyst, Cortex Search, Cortex Agents, Semantic Models, and Cortex AISQL functions to deliver actionable insights, automate business processes, and enhance decision-making capabilities. The role requires close collaboration with business stakeholders, data engineering teams, architects, and analytics groups to transform complex business requirements into secure, governed, and production-ready AI solutions. The engineer will be responsible for developing semantic layers, retrieval-augmented generation (RAG) solutions, AI-powered knowledge retrieval systems, intelligent agents, and enterprise-grade data models. Additionally, the role involves ensuring adherence to governance, security, performance optimization, and cost-management best practices within the Snowflake ecosystem.

Responsibilities

• Design and implement AI-powered analytics and business solutions using Snowflake Cortex capabilities.
• Develop and manage Semantic Models/Semantic Views to enable natural language querying and governed business metrics.
• Build and optimize Cortex Search solutions for enterprise knowledge retrieval and document intelligence.
• Design and configure Cortex Agents for intelligent orchestration of structured and unstructured data sources.
• Implement AI use cases using Cortex AISQL functions such as summarization, classification, extraction, sentiment analysis, and content generation.
• Develop AI applications using Streamlit in Snowflake (SiS), Snowsight, and Python-based frameworks.
• Create scalable data preparation pipelines, data models, and AI-ready datasets.
• Collaborate with business stakeholders to translate requirements into AI-driven solutions and measurable business outcomes.
• Apply enterprise governance, RBAC, security, monitoring, and cost optimization best practices.
• Perform testing, validation, and continuous improvement of AI models, agents, and applications.

SKILLS

Must have

• 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.

Nice to have

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.