About the role
Design, implement, and maintain clean, reliable, testable code using best practices and responsible AI-assisted development while escalating blockers early. Use AI tools responsibly across the SDLC, reviewing and validating AI-generated changes to ensure correctness and maintainability. Work with partner engineering teams, PMs, and experts (privacy, security, SRE) to understand
requirements, apply customer feedback/telemetry, and deliver scalable, reliable, user-centric features. Build extensible, maintainable services and features with strong diagnosability, reliability, and production-readiness. Participate in on-call rotations, troubleshoot live-site issues using least-privileged access, and improve TSGs, telemetry, and fixes that reduce future incidents. Contribute to engineering and operational excellence through automation, tooling, documentation, and process improvements. Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. These
requirements include, but are not limited to the following specialized security screenings: Master's Degree in Computer Science or related technical field AND 3+ 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 5+ 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 with cloud platforms (Azure, AWS, GCP), building and maintaining distributed systems including deployment, monitoring and troubleshooting of production workloads. Experience using observability tools (logging, metrics, tracing) to diagnose service issues and improve system reliability. Experience with experimentation platforms, A/B testing at scale, and statistical methodologies for measuring product impact and driving data-informed ship decisions. Familiarity with AI-assisted development workflows or responsible use of AI coding tools.
