Staff Cloud Support Engineer

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.

Cloud Support Engineer (CSE)

Snowflake seeks early-career 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.

Key Responsibilities:

As a Cloud Support Engineer , you manage customer cases and are accountable for accelerating their time-to-resolution, ensuring platform stability, and driving a world-class support experience. Operating as a full-stack technical support resource, this role blends deep hands-on troubleshooting with the customer empathy and communication skills of a trusted advisor.

Customer Value and Incident Ownership

Own the Customer Experience: Manage customer issues from initial triage through resolution and follow-up, ensuring clear communication and timely updates.

Deliver Support Value with AI: Leverage AI assistants and diagnostics to accelerate triage and root-cause analysis while maintaining accuracy and safety standards.

Outcome-Based Support: Focus on business impact, ensuring resolutions fix issues, reduce recurrence, and improve reliability.

Customer Empathy and Communication: Provide technical analysis and guidance via email, web, and phone, adapting to customer expertise levels.

Technical Execution and Collaboration

AI-Assisted Triage: Use AI to summarize logs, generate hypotheses, and draft responses—critically validating outputs before sharing.

Tooling Expertise: Utilize Snowflake environment, connectors, and internal tools to investigate and test solutions.

Cross-Functional Collaboration: Partner with Engineering, Product, and Customer Success to resolve systemic issues.

Knowledge Management: Document solutions in knowledge bases, refining AI-assisted drafts for quality.

Feedback and Innovation: Provide input on product behavior, documentation gaps, and AI-tool performance.

Bug Reporting: Document and collaborate on bugs and feature requests with engineering teams.

Operational Coverage: Support holiday/weekend rotations and on-call requirements

Required Qualifications:

BS/MS in Computer Science or equivalent experience.

2+ years in technical support (customer-facing, ideally 24x7).

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

Preferred:

Snowflake or cloud platform experience (AWS, Azure, GCP)

Advance Workflow automation / CI/CD tooling experience

AI-powered support or SRE workflow experience

Relevant certifications (SnowPro, cloud certs)

Knowledge about GPUs, CUDA, and low-level optimizations will be a plus.

Experience developing CI/CD components for production-ready MLOps pipelines.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. 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.

How do you want to make your impact?

For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com