The role involves scaling and optimizing AI models to serve large audiences across multiple cloud platforms. Responsibilities include managing the end-to-end product lifecycle, from API integration and request routing to inference execution and capacity management. The position focuses on building and maintaining validation pipelines for inference servers and load balancers to ensure performance and reliability. The work requires designing CI/CD infrastructure and analyzing observability data to identify bottlenecks and cost anomalies. The role also entails collaborating with internal teams to integrate new features and resolve cross-platform configuration issues.

Candidates must possess significant software engineering experience with a background in high-performance, large-scale distributed systems. Proficiency in building automation or test infrastructure is required, along with experience operating services on major cloud platforms. A bachelor’s degree or an equivalent combination of education, training, and experience is the minimum educational requirement. The role requires a relevant field of study as demonstrated through professional experience or coursework.