Principal Software Engineer - Parameters & Experimentation

US-CA-Menlo Park. Posted 24 days ago

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.