Snowflake

Applied AI Engineer

Snowflake2 months ago
Location

US-CA-Menlo Park

Type

Full Time

Salary

USD 126,000 – 181,700

Level

Mid

Role

Applied AI Engineer

Posted

Jan 13, 2026

Full TimeMid

The role

Summary

Applied AI Engineer position at Snowflake's Cortex AI team, building enterprise-grade AI solutions and working directly with strategic customers. This role combines hands-on development with customer advisory responsibilities, requiring 2+ years of experience and expertise in ML/AI technologies.

What you'll do

Enterprise AI Solution Architecture: Design, build, and deploy production-grade AI solutions including sophisticated AI agents for enterprise customers
End-to-End AI Lifecycle Management: Own complete implementation lifecycle from prototype development to production deployment, monitoring, and optimization
Rapid Development and Iteration: Design, iterate, and ship high-quality code and ML pipelines with velocity using Python and SQL
Customer Technical Advisory: Partner directly with customer data science and engineering teams as trusted technical advisor for AI business challenges
Cross-Functional Product Collaboration: Work with Snowflake's Product and Engineering teams to provide customer feedback and influence AI platform development
Production AI System Scaling: Deploy, monitor, and optimize AI solutions in secure, large-scale production environments
Business Challenge Translation: Convert ambiguous business objectives into robust, scalable, and performant AI solutions

What we look for

Technical

Machine Learning Pipeline DevelopmentExperience building, evaluating, and tuning ML applications and data-intensive systems
Data Science LibrariesFamiliarity with core libraries including pandas, numpy, and Snowpark
AI/ML Model ImplementationHands-on experience with machine learning model development and deployment
Programming ProficiencyStrong coding skills in Python and SQL for AI application development

Education

Bachelor's DegreeComputer Science, Engineering, related technical field, or equivalent practical experience

Experience

Software Engineering ExperienceMinimum 2+ years of professional software engineering experience
Complex Technical Problem SolvingProven ability to tackle ambiguous technical challenges using cutting-edge AI research
Fast-Paced Environment AdaptabilityDemonstrated ability to thrive in dynamic environments and adapt to evolving Generative AI landscape

Skills

Required skills

Python ProgrammingProficient coding skills for AI/ML development and data processing applications
SQL ExpertiseStrong SQL skills for data querying, transformation, and analytics
Machine Learning SystemsExperience building and tuning ML applications and data-intensive systems
Data Science LibrariesWorking knowledge of pandas, numpy, and Snowpark for data manipulation
Problem-Solving SkillsExcellent analytical and troubleshooting abilities for complex technical challenges
Communication SkillsAbility to articulate complex technical concepts to diverse stakeholders

Nice to have

Large Language Models (LLMs)Proven experience building and productionizing LLM applications
RAG and Agentic WorkflowsHands-on experience with Retrieval-Augmented Generation and autonomous AI systems
MLOps LifecycleExperience with model deployment, monitoring, and evaluation in cloud environments
Cloud PlatformsWorking knowledge of AWS, Azure, or GCP for AI/ML infrastructure
Customer-Facing ExperienceBackground in solutions architecture, sales engineering, or professional services
Startup ExperienceExperience working in fast-paced startup environments

Compensation & benefits

Salary

USD 126,000 – 181,700 (annual)

Benefits

Cutting-Edge Technology Access

Work with advanced AI tools and Snowflake's AI capabilities and infrastructure

Innovation at Scale

Opportunity to drive AI innovation while working with world-leading organizations

Professional Growth

Shape the future of AI and data cloud technology in a fast-growing company

Strategic Customer Exposure

Direct collaboration with enterprise customers and strategic business impact

Interview process

  1. 1
    Initial Screening — Phone or video call with recruiter to discuss background, experience, and role alignment
  2. 2
    Technical Assessment — Coding exercise or take-home assignment focusing on Python, SQL, and ML/AI concepts
  3. 3
    Technical Interview — Deep-dive technical discussion covering ML systems design, AI architecture, and problem-solving approach
  4. 4
    Customer Scenario Interview — Role-play exercise demonstrating ability to translate business requirements into technical solutions
  5. 5
    Final Round — Panel interview with team members and leadership focusing on cultural fit and strategic thinking
  6. 6
    Reference Check — Verification of work history and performance with previous employers or colleagues
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Snowflake

Snowflake

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Snowflake is an American cloud computing company offering data warehousing and analytics platforms.

Bozeman, Montana, United StatesFounded 2012snowflake.com

Tech Stack

Languages
PythonSQL
Frameworks
Snowparkpandasnumpy
Databases
Snowflake
Tools
Cortex AIMLOps ToolsAWS/Azure/GCP
Other
Large Language Models (LLMs)RAG (Retrieval-Augmented Generation)Agentic Workflows

Interview Guides

11 guides available for Snowflake

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