Senior Snowflake AI Architect & Platform Engineer

Machine Learning Technologies, LLC; Las Vegas (NV); On-site; USD 150,000 - 190,000; Full time

Job summary

Machine Learning Technologies, LLC in Las Vegas seeks a hands-on Engineer to design, build, and operationalize AI-powered data solutions on Snowflake, with emphasis on Cortex AI, CoCO, CoCO Desktop, and modern enterprise data platforms.

You will lead architecture reviews, PoCs, and deployments; design AI pipelines, RAG and semantic layers; and architect scalable data platforms using Snowflake, Kafka, Spark, Airflow, dbt, and cloud services.

Qualifications

• 5+ years in Data Engineering or related fields.
• Deep Snowflake architecture, security, governance, and performance.
• Hands-on with Cortex AI, CoCO, CoCO Desktop, Snowpark, and AI/ML integration patterns.
• Experience building LLM, RAG, vector search, and agentic AI solutions.
• Strong SQL and Python skills.
• Experience with Airflow, dbt, Spark, Kafka, and cloud platforms.
• Snowflake certifications preferred.
• Experience integrating OpenAI, Anthropic, Gemini or open models.

Responsibilities

• Design and implement AI-powered data solutions using Snowflake Cortex AI, CoCO, and CoCO Desktop.
• Develop and deploy RAG, agentic workflows, semantic layers, and enterprise AI applications.
• Architect scalable data platforms leveraging Snowflake, Kafka, Spark, Airflow, dbt, and cloud-native services.
• Build robust ELT/ETL pipelines and real-time integrations.
• Lead workshops, architecture reviews, PoCs, and production deployments.
• Develop reusable accelerators and best practices.

Skills

Snowflake

Python

SQL

Airflow

dbt

Spark

Kafka

Cloud platforms

Presentation skills

Tools

Cortex AI

CoCO

CoCO Desktop

Snowpark

Streamlit

Snowpipe

Dynamic Tables

Job description

Machine Learning Technologies, LLC in Las Vegas seeks a hands-on Engineer to design, build, and operationalize AI-powered data solutions on Snowflake, with emphasis on Cortex AI, CoCO, CoCO Desktop, and modern enterprise data platforms.

You will lead architecture reviews, PoCs, and deployments; design AI pipelines, RAG and semantic layers; and architect scalable data platforms using Snowflake, Kafka, Spark, Airflow, dbt, and cloud services.