We are looking for a Software Development Engineer with sound technical judgment and a bias for action who takes ownership of problems end to end, communicates clearly, and cares about operational excellence – not just launching features, but making sure they hold up at scale. Someone who naturally raises the bar for the team: mentoring junior developers, advocating engineering best practices, and thinking beyond the immediate sprint.
Key job responsibilities
– Design, build, test, and operate production AI features used by multiple teams and operating at our scale.
– Deliver end-to-end solutions with focus on maintainability, scalability, performance, and reliability.
– Collaborate with Product and Science to define experiences, run experiments, and iterate based on data.
– Build AI-powered experiences including personalized recommendations, relevance explanations, and knowledge-driven features using LLMs and generative AI.
– Define and implement measurement strategies including analytics events and experiment configurations to track engagement and retention.
– Navigate ambiguity and make sound technical decisions in a problem space where established patterns don't always apply.
Basic Qualifications
– Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.
– 5+ years of non-internship professional software development experience
– Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design.
– Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
– Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
Preferred Qualifications
– Experience building server-side rendered web experiences (SSR) and performance-oriented UI rendering patterns.
– Experience with experimentation (A/B testing), analytics instrumentation, and metrics-driven iteration.
– Familiarity with AI/ML integration and generative AI applications.
– Experience with end-to-end SDLC ownership, including operations and on-call, monitoring/metrics, and incident response/RCA.
– Experience mentoring engineers and driving engineering best practices.












