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About the Role
Snowflake seeks Cloud Support Engineers who combine technical expertise, customer empathy, and an AI-first mindset. You'll leverage and refine AI tools to accelerate troubleshooting, improve knowledge bases, and reduce time to resolution—safely and responsibly. Experience in 24x7 technical support, escalation handling, on-call rotations, and incident management is ideal.
Responsibilities
- Manage customer cases and are accountable for accelerating their time-to-resolution, ensuring platform stability, and driving a world-class support experience.
- Manage customer issues from initial triage through resolution and follow-up, ensuring clear communication and timely updates.
- Leverage AI assistants and diagnostics to accelerate triage and root-cause analysis while maintaining accuracy and safety standards.
- Focus on business impact, ensuring resolutions fix issues, reduce recurrence, and improve reliability.
- Provide technical analysis and guidance via email, web, and phone, adapting to customer expertise levels.
- Use AI to summarize logs, generate hypotheses, and draft responses—critically validating outputs before sharing.
- Utilize Snowflake environment, connectors, and internal tools to investigate and test solutions.
- Partner with Engineering, Product, and Customer Success to resolve systemic issues.
- Document solutions in knowledge bases, refining AI-assisted drafts for quality.
- Provide input on product behavior, documentation gaps, and AI-tool performance.
- Document and collaborate on bugs and feature requests with engineering teams.
- Support holiday/weekend rotations and on-call requirements.
Requirements
- BS/MS in Computer Science or equivalent experience.
- 2+ years in technical support (customer-facing, ideally 24x7).
- Fluency in Japanese (spoken and written) and familiarity with Japanese business culture; experience living or working in Japan preferred.
- Strong AI fluency, including prompt engineering, context management, and the ability to critically validate AI outputs and know when to fall back to manual investigation.
- Experience with AI-powered tooling (e.g., coding assistants/agentic IDEs) and modern support environments.
- Solid technical troubleshooting skills, including comfort with SQL, log analysis, and scripting/automation (e.g., Python, APIs, workflow tools) to diagnose issues and streamline tasks.
- SQL, log analysis, and scripting skills (Python, APIs).
- Strong written/verbal English communication.
- Basic understanding of Windows and Linux Operating Systems.
- Basic understanding of Data Warehousing fundamentals and concepts.
- Ability to write and understand basic SQL queries.
- Familiarity with end-to-end ML pipeline including ML modeling, feature engineering, ML model training, etc.
- Familiarity with prompt engineering, and associated tools within the LLM ecosystem, including Langchain, vector databases, co-pilot, and open-source Hugging Face models.
- Being able to troubleshoot and resolve issues related to MLOps pipelines, model performance, and infrastructure.
- Familiarity with RESTful APIs and web services.
- Snowflake or cloud platform experience (AWS, Azure, GCP) is preferred.
- Advance Workflow automation / CI/CD tooling experience is preferred.
- AI-powered support or SRE workflow experience is preferred.
- Relevant certifications (SnowPro, cloud certs) are preferred.
- Knowledge about GPUs, CUDA, and low-level optimizations will be a plus.
- Experience developing CI/CD components for production-ready MLOps pipelines is preferred.
Skills
- AI fluency
- Prompt engineering
- Context management
- Technical troubleshooting
- SQL
- Log analysis
- Scripting
- Automation
- Python
- APIs
- Workflow tools
- English communication
- Windows Operating Systems
- Linux Operating Systems
- Data Warehousing fundamentals
- SQL queries
- ML pipeline
- ML modeling
- Feature engineering
- ML model training
- Langchain
- Vector databases
- Co-pilot
- Hugging Face models
- MLOps pipelines
- Model performance
- Infrastructure troubleshooting
- RESTful APIs
- Web services
- Snowflake experience
- Cloud platform experience (AWS, Azure, GCP)
- Workflow automation
- CI/CD tooling
- AI-powered support
- SRE workflow
- SnowPro certification
- Cloud certifications
- GPUs
- CUDA
- Low-level optimizations
Location
- Toronto, ON
- Atlanta, GA
Work Type
- 24x7 technical support
- On-call rotations
Experience Level
- 2+ years in technical support
Education Level
- BS/MS in Computer Science or equivalent experience
About the Company
- Snowflake is powering the era of the agentic enterprise.
- We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.