Principal Software Engineer - Parameters & Experimentation

The role

You will architect and build distributed infrastructure for configuration and feature-flagging services. You will also build experimentation infrastructure and embed AI-powered capabilities into the platform.

What you will do

• Architect and build distributed infrastructure.
• Design scalable configuration and feature-flag services.
• Build automated validation, targeted exposure, progressive rollouts, health-based guardrails, and dependable rollback.
• Partner with engineering and data science teams to build assignment, exposure tracking, and measurement infrastructure.
• Embed AI-powered capabilities into the platform for configuration discovery, risk assessment, rollout planning, and impact analysis.
• Translate ambiguous needs into practical designs and milestones.
• Deliver intuitive APIs, libraries, and self-service tools.
• Write and review production code.
• Diagnose complex failures and own operational outcomes.
• Mentor engineers.

Required qualifications

• 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.
• Strong understanding of concurrency, consistency, caching, failure recovery, and performance.
• Strong computer science fundamentals.
• Hands-on proficiency in Java, Go, C++, or a comparable backend language.
• Experience with AWS, Azure, or Google Cloud.
• An AI-first engineering practice.
• A track record of turning ambiguous problems into delivered systems.
• Clear written communication.
• Low-ego collaboration.
• Strong ownership.
• Experience mentoring senior engineers.

Nice to have

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

About the company

Snowflake's AI Data Cloud supports critical enterprise workloads across multiple clouds and regions.