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At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.

Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.

Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.

eBay’s Advertising and Marketing Technology teams build platforms, services, and user experiences that help sellers and advertisers grow their businesses and bring new and existing customers to eBay.

As a Staff Software Engineer, you will work on high-scale systems spanning frontend applications, backend services, APIs, data pipelines, and AI-assisted engineering workflows. You will partner with product, design, analytics, and applied science teams to turn business problems into reliable, maintainable software with measurable customer and seller impact. You will guide technical decisions, mentor engineers, and take ownership of complex features from design through production in a fast-moving, collaborative environment.

• Build advertising and marketing capabilities that help sellers and advertisers grow their businesses and improve the experience for eBay customers.
• Develop scalable, highly available applications, APIs, and services using technologies such as Marko, React, Node.js, Java, and Scala.
• Own the delivery of complex features from technical design and architecture through deployment, production support, and continuous improvement, with a focus on performance and quality.
• Guide system design and technical decisions across teams, evaluating tradeoffs and building agreement on scalable, reliable, and maintainable solutions.
• Use AI-assisted development tools throughout coding, debugging, testing, and code review to improve engineering productivity.
• Collaborate with machine learning engineers on AI-powered advertising and marketing features, including large language model (LLM) integrations, recommendation systems, and intelligent campaign optimization.
• Mentor team members, contribute to technical discussions, and help shape engineering best practices that support continuous learning, agile development, open-source collaboration, and rapid software delivery.