MTS 2, Software Engineer, Backend

eBay•Toronto, ON

About The Position

The Search Backend team at eBay builds and operates the core services powering eBay Search at scale. We develop reliable, high-performance backend systems that retrieve, rank, and serve relevant results for a large global audience of buyers. These systems are crucial for helping users quickly find what they want and enabling excellent end-to-end shopping experiences. Our work is central to eBay’s marketplace and directly impacts customer satisfaction, seller success, and business growth. We are increasingly adopting AI-driven and AI-assisted approaches to enhance how search systems are built, optimized, and evolved. We are seeking a Member of Technical Staff 2, Backend to lead the invention and delivery of server-side functionality, improving how shopper intent is translated into fast, relevant, and reliable search experiences. In this role, you will own a functional area, driving technical execution from build through production. You will collaborate across product, engineering, and scientific research to deliver scalable, high-quality solutions with measurable impact. You’ll also help the team adopt AI-first engineering practices and modern development workflows to improve productivity, quality, and customer outcomes. The Search team fosters a collaborative, transparent, and inclusive culture where every voice is valued, and collective growth is celebrated.

Requirements

Strong backend development experience in Java (Java 17+ preferred) and production service development with Spring Boot or similar frameworks.
Skilled in crafting extensible, maintainable, and scalable systems designed for high-traffic environments.
8+ years of hands-on involvement in Java, Spring/Springboot, REST APIs, messaging systems and/or other backend programming languages.
An AI-first attitude, with experience or strong interest in leveraging AI-assisted development and testing tools to accelerate delivery, improve quality, and help drive responsible AI workflows across the team.
Experience owning multiple subsystems or a major functional area across design, implementation, testing, deployment, monitoring, and production support in a large, modular codebase.
Proven ability to convert product goals and business requirements into practical technical builds and execution plans.
Proficient at designing scalable backend solutions.
Makes sound trade-offs across complexity, performance, and long-term maintainability.
Strong understanding of distributed systems fundamentals, including API design, latency and throughput trade-offs, resilience patterns, scalability, reliability, and observability through metrics, logging, and tracing.
Strong communication and collaboration skills, with the ability to influence technical direction, clarify trade-offs, align cross-functional partners, and drive execution across teams and dependencies.

Nice To Haves

Experience with search and retrieval concepts such as query processing, ranking and sorting, facets and aspects, workflow orchestration systems, or relevance experimentation frameworks.
Solid understanding of GraphQL
Experience with Kafka

Responsibilities

Design and deliver backend capabilities that turn shopper intent into optimized search queries and high-quality search results at scale.
Lead a key operational segment covering architecture, development, verification, rollout, supervision, and operational excellence in production.
Develop technical compositions, execution plans, and scalable solutions based on product goals and business requirements that balance time to market with long-term quality, maintainability, and extensibility.
Partner across multiple engineering, product, and applied science teams to define interfaces, evaluate trade-offs, resolve dependencies, and drive measurable improvements in relevance, latency, reliability, and developer efficiency.
Raise the quality and scalability of the team’s systems by driving observability, test automation, resilience, and continuous improvement in code, architecture, and operational practices.
Proactively identify and address technical debt, design gaps, and workflow inefficiencies before they become blockers, helping the team move faster and operate more effectively at scale.