Join Rippling's Variable Compensation team as a key technical leader, driving innovation in our finance platform. This role offers high visibility and significant growth opportunities. You will be instrumental in architecting scalable systems, enhancing existing features, and delivering high-quality, reliable financial services.

This is an exceptional chance to contribute to an AI-first product, navigating ambiguous requirements and building a robust, intuitive compensation platform from the ground up. The team operates at the intersection of Finance, HR, and Artificial Intelligence, focusing on areas like the Compensation Engine, Payment Orchestration, and AI-First Design with Explainability.

Architect and lead the development of internet-scale, highly distributed systems and scalable services. Engage in hands-on coding and code reviews, leveraging languages like Python, Golang, and Java. Provide visionary technical leadership, establishing engineering best practices and guiding technology adoption. Mentor engineers, fostering a culture of continuous learning and technical excellence. Design systems capable of handling millions of concurrent users with high performance and reliability.

Develop clean, modular APIs and programmatic interfaces. Implement analytical and transactional storage systems at petabyte scale. Ensure high availability and reliability with target uptimes of four or five 9s. Integrate comprehensive observability practices, including monitoring, logging, and tracing. Build and integrate streaming solutions and workflow systems. Collaborate with cross-functional teams to achieve strategic goals and drive product innovation.

A minimum of 9 years of software engineering experience is required, with a strong emphasis on large-scale distributed systems. Proficiency in Python, Golang, and Java is essential, alongside a deep understanding of distributed computing, data architecture, and scalable system design. Demonstrated experience in technical leadership roles, including mentoring engineering teams, is crucial.

Extensive experience building systems for millions of users, understanding SLAs, system resiliency, and observability is necessary. Expertise in designing and implementing abstraction APIs and programmatic APIs, including BFF systems, is required. Proficiency with both analytical (e.g., Presto, S3, Snowflake) and transactional (e.g., MySQL, Aurora, MongoDB) storage systems is essential. Experience with public cloud platforms and streaming technologies like Spark Streaming, Apache Flink, and Kafka Connect is expected.

Familiarity with transactional and analytical workflow systems is needed. Excellent communication skills are vital for conveying complex technical concepts. Experience integrating AI-assisted workflows and the ability to quickly understand and navigate large codebases to drive solutions for ambiguous requirements are highly valued.