> Markdown version of [/jobs/ext/4635056-sr-staff-software-engineer](https://www.wearedevelopers.com/jobs/ext/4635056-sr-staff-software-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Staff Software Engineer - **Company:** PayPal - **Location:** New York, NY, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Cloud Computing, Distributed Systems, Spring Framework, Machine Learning, Object-Oriented Software Development, Recommender Systems, Software Engineering, Google Cloud, Large Language Models, Event Driven Architecture, Kubernetes, Information Technology, Real Time Data, Apache Kafka, Graphql, Restful APIs, Docker, Microservices - **Published:** November 8, 2026 - **Apply:** https://www.juju.com/job/28_25303_da4d57eefd12554d244364ceb7f22960 ## About the Role Lead the architecture and development of scalable, AI-driven personalization and recommendation capabilities, using real-time data and customer context to improve engagement, retention, and conversion. Set technical strategy across teams, deliver reliable production software, and partner with product management to develop customer-focused solutions. Requirements: Requires a bachelor's degree in Computer Science, Software Engineering, or a related field and at least 12 years of progressively responsible experience. Candidates must have extensive experience with Java and Spring, distributed cloud-native systems, APIs, event-driven architectures, personalization and machine learning, production AI/LLM systems, observability, and cross-team technical leadership. Key Skills: Java, Spring, Object-Oriented Design, Distributed Systems, Microservices, REST, GraphQL, Docker, Kubernetes, Google Cloud Platform, Apache Kafka, Behavioral Analytics, Personalization Systems, Recommendation Systems, Machine Learning, Large Language Models