Senior Software Engineer Full Stack AI ML United States Washington Redmond

Job description

Partner across multiple product groups to apply subject-matter expertise in distributed systems design practices, interactions between cloud technology layers and components, basic dependencies at scale, and the code that defines infrastructures. Lead by example and mentor others to produce extensible and maintainable code used across products. Develop and evangelize insights, best practices, and standards that can be applied to improve system, platform, and/or product development and operations across the business. Drive continuous improvements in the architecture, code, features, operations and comprehensive use scenarios of products by leveraging end-to-end technical expertise. Make improvements to the product fundamentals and architecture, share knowledge and code, always looking for ways to make what we build useful to multiple teams and products. Demonstrate end-to-end expertise in distributed systems design, interactions between cloud technology layers. Provide technical leadership in test maturity reviews, static analysis reviews, meetings, on-call rotations, and incident responses throughout product development and operations cycles. Provides deep business and technical expertise as required to resolve major incidents. 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 with Artificial Intelligence (AI), Machine Learning (ML), risk assessment systems, or intelligent automation solutions. (Appropriate for the R2D and Automated Risk Assessment space. Experience with DevOps practices, continuous integration and continuous deployment (CI/CD), infrastructure as code, and service reliability engineering. Experience analyzing large datasets and translating insights into product or engineering improvements. Experience leading technical initiatives and influencing architecture, design, and engineering best practices across teams. Demonstrated ability to drive operational excellence through automation, scalability, reliability, and continuous improvement.