Sr Staff Software Engineer

PayPal•New York, NY

3d•$246,305 - $333,500•Hybrid

About The Position

PayPal, Inc. seeks Sr Staff Software Engineer in New York, NY. This role will lead the design, development, and implementation of intelligent, AI-driven software applications and features across PayPal’s digital ecosystem, delivering seamless and frictionless customer experiences. The engineer will leverage real-time data, behavioral analytics, and AI-driven decision-making to improve engagement, retention, and conversion. Responsibilities include building scalable, personalized application features that adapt dynamically to user context, and architecting cloud-native, scalable systems that balance performance, reliability, and security while enabling rapid experimentation and innovation. The role also involves driving the adoption of personalization frameworks and tools, establishing and executing the long-term technical strategy for the personalization platform, and anticipating and capitalizing on emerging trends in personalization, recommendation systems, and agentic AI. The engineer will make technical decisions affecting multiple teams, develop automated tests, and deliver high-quality software code in a continuous integration and delivery environment. Collaboration with product management to ideate solutions to business problems is also a key aspect of this role. Partial telecommuting is permitted from within a commutable distance.

Requirements

Bachelor’s degree, or foreign equivalent, in Computer Science, Software Engineering, or a closely related field plus 12 years of progressively responsible experience in the job offered or a related occupation.
Experience designing and developing large-scale software applications using Object-Oriented Design and Java, including Spring and related enterprise frameworks (8 years)
Experience designing and operating large-scale distributed systems with high availability, scalability, and fault tolerance using microservices-based architectures (8 years)
Experience designing and implementing service-oriented and API-based architectures using REST and GraphQL, including schema design and API governance (8 years)
Experience building shared backend platforms and reusable frameworks used by multiple engineering teams (8 years)
Experience building cloud-native systems using containerization and orchestration technologies such as Docker and Kubernetes, deployed on cloud platforms including Google Cloud Platform (GCP) (7 years)
Experience designing and implementing real-time, event-driven architectures using messaging and streaming technologies such as Apache Kafka, AMQ, or equivalent systems (7 years)
Experience working with large-scale customer data, behavioral analytics, and feature engineering using distributed data processing platforms and cloud-based data services (7 years)
Experience developing personalization and recommendation systems using rule-based systems and machine learning techniques, including ranking and decisioning logic (6 years)
Experience integrating, deploying, and operating machine learning models in production using ML platforms such as Google Vertex AI, including model training, serving, and lifecycle management (5 years)
Experience designing and deploying AI-driven decisioning systems that leverage predictive models, real-time context, and experimentation frameworks (5 years)
Experience developing and integrating Large Language Model (LLM)–based systems using cloud AI platforms, including prompt orchestration, tool or function calling, and evaluation in production environments (4 years)
Experience designing and operating observability solutions for distributed systems, including logging, metrics, tracing, alerting, and reliability monitoring using industry-standard observability tools (6 years)
Experience designing AI-powered systems with privacy, security, explainability, and governance requirements in regulated environments (6 years)
Experience driving technical strategy and architectural decisions that span organizational boundaries, mentoring engineers, and influencing cross-functional stakeholders on system design trade-offs and personalization best practices (5 years).

Responsibilities

Lead the design, development, and implementation of intelligent, AI-driven software applications and features across PayPal’s digital ecosystem.
Leverage real-time data, behavioral analytics, and AI-driven decision-making to improve engagement, retention, and conversion.
Build scalable, personalized application features that deliver real-time personalization capabilities that adapt dynamically to user context.
Architect cloud-native, scalable systems that balance performance, reliability, and security while enabling rapid experimentation and innovation.
Drive the adoption of personalization frameworks and tools across teams, enabling consistency, reliability, and faster product integration.
Establish and execute the long-term technical strategy for the personalization platform, ensuring alignment with company-wide goals and customer-first principles.
Anticipate and capitalize on emerging trends in personalization, recommendation systems, and agentic AI to maintain a competitive advantage.
Make technical decisions affecting multiple teams, crossing organizational boundaries.
Develop automated tests and deliver high-quality software code to production within a short development cycle in the continuous integration and delivery environment.
Partner with product management to ideate solutions to business problems.