Senior Software Engineer

This senior backend engineering role within Reddit's Ads organization works across teams focused on ad safety, creative management, and brand innovation. The engineer will build microservices, distributed systems, and real-time data infrastructure for the advertising platform, collaborating with product managers and data teams. Requires 3+ years of software development experience in languages like Java, Scala, Go, C++, or Python, with ownership of features or projects.

This role designs and maintains highly scalable components for Kayzen's real-time bidding platform, including budget systems, event processing, and data pipelines. The Senior Software Engineer will work with Java, SQL, and NoSQL databases, and is expected to use AI development tools like Claude Code and GitHub Copilot. The role requires deep expertise in distributed systems, multi-threading, and JVM internals.

This Senior Backend Engineer role focuses on building and maintaining high-performance, low-latency services for real-time ad recommendation and data serving in the Ad Cloud. The engineer will optimize system components, manage database scaling, and enhance observability, requiring 3-5+ years of backend experience with Go or Python and strong distributed systems knowledge.

This role designs and builds backend systems that ingest, correlate, enrich, and serve billions of records across PitchBook's customer-facing products. The engineer will own features and system components end-to-end, from requirements through design, implementation, testing, and production support. Requires 5+ years of software engineering experience, 5+ years of Java development including production microservices, and 4+ years with Spring Boot/Spring Framework.

This Senior Software Engineer role focuses on building and integrating machine learning systems, with challenges in model deployment and scalability. The engineer will work on AI/ML product features, likely using frameworks like TensorFlow or PyTorch.

This role leads the architecture and development of Cardlytics' core data and AI infrastructure on the Databricks platform, focusing on distributed systems scalability and platform reliability. The engineer will utilize Apache Spark, Delta Lake, and MLflow to build scalable data pipelines and machine learning workflows.

This role drives new business sales for partner acquisition, focusing on a hunt-oriented go-to-market motion to build the partner ecosystem. It involves identifying and closing new partnerships to expand Cardlytics' network, likely targeting retailers and other data partners.