Principal Software Enginner - Parameters & Experimentation

Snowflake • Menlo Park, CA

5d • $264,000 - $379,500

About The Position

Snowflake’s Parameters & Experimentation team builds configuration, feature-flagging, and experimentation infrastructure that enables engineers to introduce capabilities, control exposure, and measure outcomes. The Principal Software Engineer will help build the platform’s next generation, combining distributed-systems engineering with an AI-first approach to developer productivity and operational intelligence. This hands-on role shapes technical direction, solves complex systems problems, and leads initiatives across engineering teams to support faster customer value through safe delivery and trustworthy experimentation.

The role includes architecting scalable configuration and feature-flag services; developing safeguards and automated rollout capabilities; advancing experimentation infrastructure; incorporating AI into software development and platform capabilities; delivering APIs, libraries, and self-service tools; and guiding migrations and adoption. The engineer also writes and reviews production code, diagnoses complex failures, owns operational outcomes, and mentors engineers.

Requirements

• 12+ years of software engineering experience, including technical leadership of complex backend or infrastructure initiatives spanning multiple teams.
• Deep experience designing, building, and operating large-scale distributed systems, with strong understanding of concurrency, consistency, caching, failure recovery, and performance.
• Strong computer science fundamentals and hands-on proficiency in Java, Go, C++, or a comparable backend language.
• Experience with AWS, Azure, or Google Cloud.
• Actively use AI throughout the software lifecycle and be able to demonstrate improvements to execution, problem-solving, and quality; be ready to build AI-powered platform capabilities and help others adopt this approach.
• Track record of turning ambiguous problems into delivered systems, balancing architectural investments with incremental progress, and driving adoption across engineering organizations.
• Clear written communication, low-ego collaboration, strong ownership, and experience mentoring senior engineers.
• Degree in Computer Science or a related field, or equivalent practical experience.

Nice To Haves

• Experience with feature-flag or configuration platforms, distributed control planes, progressive delivery, experimentation infrastructure, or AI-powered developer tools.

Responsibilities

• Architect and build scalable distributed configuration and feature-flag services with low-latency evaluation, clear consistency guarantees, fault isolation, and predictable failure behavior.
• Develop automated validation, targeted exposure, progressive rollouts, health-based guardrails, and dependable rollback to make changes observable, auditable, and recoverable while reducing manual coordination.
• Partner with engineering and data science teams to build reliable assignment, exposure-tracking, and measurement infrastructure for evaluating changes and making evidence-based decisions.
• Use AI throughout the design, implementation, testing, and operation of software; build AI-powered platform capabilities for configuration discovery, risk assessment, rollout planning, and impact analysis; establish evaluation, security, and reliability standards; and promote AI-first practices.
• Translate ambiguous needs into practical designs and milestones; deliver intuitive APIs, libraries, and self-service tools; guide incremental migrations; and simplify the lifecycle from feature-flag creation to retirement.
• Write and review production code, diagnose complex failures, own operational outcomes, and mentor engineers.
• Influence teams through technical depth, clear communication, and sound judgment.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal