Principal Experimentation Software Engineer

Microsoft•Redmond, WA

About The Position

Collaborate and influence designs, architectures, and best practices to support large-scale distributed systems and big data pipelines in our A/B testing platform. Analyze complex, high-volume, high-dimensional data systems for scalability. Understand and influence the product metrics in Experimentation AB across different surfaces where MS Teams is available. Collaborate closely with peers and other teams across a variety of technical, business and data backgrounds to find innovative solutions in a fast-paced environment. Leverage AI to accelerate and optimize experimentation workflows, data pipelines, and developer experiences, improving speed, quality, and reliability. Be a champion and influencer of our experimentation-driven culture within MS Teams.

Requirements

Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
6+ years of experience designing and developing big data distributed architectures, scalable systems, and solving complex data problems at scale.
4+ years of experience building and managing A/B experimentation platform capabilities integrated with big data systems, as well as hands-on experience utilizing A/B testing.
Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 10+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Deep experience in system design and architecture for large scale, distributed, highly available services, with a strong record of operational excellence, reliability, performance optimization, efficiency, and ownership of production systems.
Proven ability to apply AI and machine learning for acceleration and optimization of experimentation workflows, data pipelines, guardrails, and data informed decision making.
Leadership and influence across organizational boundaries, with the ability to communicate technical details clearly to diverse audiences, strong analytical skills and data storytelling through concise, actionable visualizations, a bias for action and customer focus, and the ability to navigate ambiguity in a fast-paced environment.