Staff Software Engineer (AI)

Location: Menlo Park, California, United States

Salary: $236K–$339.2K per year

Company

Snowflake builds cloud data platforms and globally distributed data warehouse infrastructure for business, engineering, data science, and customer operations.

What you will do

• Provide hands-on technical guidance, conduct code reviews, develop engineers, raise engineering quality standards, and establish best practices.
• Design and implement highly available distributed platforms, pipelines, and data infrastructure components for global data processing.
• Lead cross-functional engineering projects from inception through implementation and production deployment across multiple quarters and teams.
• Partner with product managers, senior individual contributors, data science teams, and business units to deliver end-to-end data platform capabilities.
• Own or co-own reliability, observability, SLOs, capacity, and durable remediation for the assigned problem space.
• Use AI-assisted engineering responsibly to improve velocity and quality.

Requirements

• 12+ years of software development experience in distributed systems, with a strong focus on data warehouse or data infrastructure engineering.
• Deep experience developing resilient, large-scale services in public cloud environments such as AWS, Azure, or GCP.
• Demonstrated proficiency in distributed systems architecture and database fundamentals, with experience solving complex system design challenges.
• Excellent technical communication and collaborative problem-solving skills across multidisciplinary teams.
• BS, MS, or PhD in Computer Science or a related technical field, or equivalent practical experience.
• Ability to understand Snowflake internals and user needs, anticipate future requirements, lead at scale, and collaborate across teams on reliability and efficiency.
• Ability to comply with confidentiality and security standards and protect customer information.

Nice to have

• Familiarity with data or ML orchestration systems across diverse architectures.

Culture & Benefits

• AI-assisted engineering is treated as a core part of problem-solving and delivery.
• Work in a fast-moving, experimental environment that encourages testing emerging capabilities.
• Collaborative, low-ego culture focused on challenging ordinary thinking and accelerating innovation.
• Employees must follow confidentiality and security standards for sensitive and customer data.