Senior Software Engineer - Backend

Lead design and implementation of scalable, high-performance backend systems operating under strict latency and reliability requirements. Drive platform modernization and long-term sustainability of critical services, improving code quality, maintainability, and operational safety. Ensure performance, scalability, and stability of the service as traffic, data volume, and business requirements continue to grow. Define and evolve instrumentation, observability, and experimentation capabilities to support data-driven decision making and safe production changes. Collaborate closely with cross-functional partners (engineering, data science, experimentation, product, and infrastructure) to align technical solutions with business goals. Provide technical leadership and mentorship, influencing architecture decisions and engineering best practices across teams. Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python Master'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 OR Bachelor'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 equivalent experience. Experience working on high-throughput, production systems where scalability, latency, and stability are critical. Demonstrated ability to design, evolve, and maintain complex systems over time. Experience collaborating with cross-functional teams to deliver solutions aligned with business needs. Problem-solving skills and ability to analyze and address performance or reliability issues in production environments. Experience with real-time bidding systems, ad tech, or high-frequency decision systems. Familiarity with experimentation platforms, A/B testing, or traffic shaping systems. Experience working with ML-driven decision systems or integrating models into production pipelines. Exposure to large-scale data processing or feature pipelines. Experience with cloud environments and modern deployment practices.