Principal Software Enginner - Parameters & Experimentation

Architect and build distributed infrastructure. Design scalable configuration and feature-flag services with low-latency evaluation, clear consistency guarantees, fault isolation, and predictable behavior during failures.

Make a safety scale with change velocity. Build automated validation, targeted exposure, progressive rollouts, health-based guardrails, and dependable rollback. Reduce manual coordination while making changes observable, auditable, and recoverable.

Advance experimentation. Partner with engineering and data science teams to build reliable assignment, exposure tracking, and measurement infrastructure that helps teams evaluate changes and make evidence-based decisions.

Build and work AI-first. Make AI integral to how you design, implement, test, and operate software. Embed AI-powered capabilities into the platform for configuration discovery, risk assessment, rollout planning, and impact analysis. Establish rigorous evaluation, security, and reliability standards for these capabilities, and drive adoption of AI-first practices across the team.

Lead from architecture through adoption. Translate ambiguous needs into practical designs and milestones. Deliver intuitive APIs, libraries, and self-service tools; guide incremental migrations and simplify the full lifecycle from flag creation to retirement.

Raise the engineering bar. Write and review production code, diagnose complex failures, own operational outcomes, and mentor engineers. Influence across teams through technical depth, clear communication, and sound judgment.

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, plus experience with AWS, Azure, or Google Cloud.

An AI-first engineering practice: you actively use AI throughout the software lifecycle and can demonstrate how it improves your execution, problem-solving, and quality. You are ready to build AI-powered platform capabilities and help others adopt this approach.

A 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.

A degree in Computer Science or a related field, or equivalent practical experience.

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

Help build the systems that let engineers innovate faster than manual processes can support, with the evidence and safeguards that critical workloads demand.

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