Cloud Support Engineer (AI)

Location: Toronto, Ontario, Canada or Atlanta, Georgia, United States

Compensation: CA$90K–CA$112K annually

Company

Snowflake provides a cloud data platform and is developing AI-native ways to improve how work is performed across the organization.

What you will do

• Manage customer cases from initial triage through resolution and follow-up, maintaining clear communication and timely updates.
• Use AI assistants and diagnostic tools to summarize logs, generate troubleshooting hypotheses, accelerate root-cause analysis, and draft responses while validating outputs for accuracy and safety.
• Provide full-stack technical support through email, web, and phone, focusing on business impact, platform stability, and reducing recurring issues.
• Investigate Snowflake environments, connectors, and internal tools, including SQL, logs, scripting, APIs, and workflow tools.
• Collaborate with Engineering, Product, and Customer Success on systemic issues, bugs, feature requests, and product feedback.
• Document solutions in knowledge bases, refine AI-assisted content, and participate in holiday/weekend rotations and on-call coverage.

Requirements

• BS/MS in Computer Science or equivalent experience.
• At least 2 years of customer-facing technical support experience, ideally in a 24x7 environment.
• Fluency in spoken and written Japanese, familiarity with Japanese business culture, and strong written and verbal English communication. Experience living or working in Japan is preferred.
• AI fluency, including prompt engineering, context management, critical validation of AI outputs, and the ability to return to manual investigation when appropriate.
• Experience with AI-powered tooling, such as coding assistants or agentic IDEs, and modern support environments.
• Technical troubleshooting skills covering SQL, log analysis, scripting and automation, including Python, APIs, and workflow tools.
• Basic understanding of Windows and Linux operating systems, data warehousing fundamentals, and basic SQL queries.
• Familiarity with end-to-end ML pipelines, including modeling, feature engineering, and model training; prompt engineering and LLM ecosystem tools such as LangChain, vector databases, copilots, and open-source Hugging Face models.
• Ability to troubleshoot and resolve MLOps pipeline, model performance, and infrastructure issues; familiarity with RESTful APIs and web services.

Nice to have

• Snowflake or cloud platform experience with AWS, Azure, or GCP.
• Advanced workflow automation or CI/CD tooling experience.
• AI-powered support or SRE workflow experience.
• Relevant certifications, such as SnowPro or cloud certifications.
• Knowledge of GPUs, CUDA, and low-level optimizations.
• Experience developing CI/CD components for production-ready MLOps pipelines.

Culture & Benefits

• AI-first, experimental approach focused on safely using AI to accelerate troubleshooting and improve support outcomes.
• Fast-moving environment that values curiosity, low-ego collaboration, challenging ordinary thinking, and innovation.
• Operational coverage includes holiday/weekend rotations and on-call requirements.