AI Native Software Engineer, Risk

eBay • Austin, TX

23h

About The Position

eBay is seeking a hands-on Software Engineer to build and operate platforms and services that enable smarter risk decisions, seamless automation, and resilient workflows at scale. The role is part of Global Payments and Risk, which builds products and platforms for safer, more trusted commerce using data, modern software architectures, and AI-native engineering practices. The engineer will deliver scalable, reliable, and secure systems for Risk Engineering, applying AI where it improves product quality, operational efficiency, and engineering productivity. This role carries end-to-end ownership of production systems, from design and implementation through launch, operations, and continuous improvement.

The position involves building AI-enabled systems and workflows using capabilities such as LLMs, retrieval, tool use, structured outputs, deterministic logic, and human review. It also includes developing backend services, APIs, and integrations for risk decisioning, investigation, and automation; defining quality measures for AI behavior; and improving production reliability, scalability, latency, security, and cost efficiency. The engineer will collaborate with engineering, product, data science, analytics, and operations teams.

The role offers the opportunity to work on high-impact systems that help make commerce safer at scale and to build practical AI-enabled capabilities with strong engineering rigor and real-world impact. The listed base pay range is $98,000–$173,600; compensation may vary based on location, skills, and experience. Total compensation may include a target bonus, restricted stock units as applicable, and benefits. Remote roles are not eligible for U.S. visa sponsorship.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• At least 4 years of software engineering experience building and operating production systems.
• Strong proficiency in at least one backend language, such as Python, Java, or TypeScript.
• Experience building and shipping backend services or product features, including design, implementation, testing, launch, and production support.
• Experience building and shipping modern AI capabilities in production or at meaningful scale, such as LLM-based workflows, tool calling, retrieval, structured outputs, workflow automation, or knowledge-grounded product experiences.
• Experience designing reliable AI-powered workflows, including prompt or context design, output validation, fallback behavior, and iterative quality improvement.
• Strong understanding of APIs, service integrations, data flows, logging, monitoring, and production debugging; familiarity with distributed systems concepts.
• Ability to make sound engineering trade-offs across reliability, latency, scalability, cost, and developer velocity.
• Strong written and verbal communication skills and ability to work effectively across engineering, product, design, and other cross-functional partners.

Nice To Haves

• Experience building or contributing to agentic or tool-using workflows with clear guardrails and bounded autonomy.
• Experience with AI-output evaluation workflows, including automated graders, benchmark tasks, error analysis, or human-in-the-loop review.
• Familiarity with search, retrieval, ranking, embeddings, or other knowledge-grounded AI patterns.
• Familiarity with secure execution practices, scoped credentials, auditability, and safe handling of AI-driven actions.
• Experience using AI to improve engineering workflows, including development, testing, debugging, or operational tooling.
• Experience instrumenting and improving systems through monitoring, experimentation, and iterative analysis of failures or regressions.
• Experience in fraud, trust, payments, risk, or other decisioning-heavy domains.
• Ability to collaborate effectively on small technical initiatives; mentoring experience is a plus.

Responsibilities

• Design, build, test, deploy, and support production-ready AI-enabled systems for customer and business problems in Risk Engineering.
• Build end-to-end services and workflows combining LLMs, retrieval, tool use, structured outputs, deterministic logic, and human review where appropriate.
• Develop scalable backend services, APIs, and integrations for risk decisioning, investigation, and automation.
• Translate business and operational needs into technical designs, delivery plans, and measurable outcomes.
• Own a functional area end to end, including implementation, launch readiness, observability, monitoring, and continuous improvement.
• Define and maintain quality standards for AI behavior using task-level evaluations, offline and online metrics, regression detection, and release criteria.
• Improve production systems' reliability, scalability, latency, security, and cost efficiency.
• Drive operational readiness through fallback strategies, rollback paths, incident handling, and runbooks.
• Partner with engineering, product, data science, analytics, and operations teams to deliver robust, well-governed solutions.
• Contribute code, design documents, and test plans, and improve engineering standards through reviews and documentation.

Benefits

• Medical, financial, and other benefits, including 401(k) eligibility and paid time off benefits such as PTO and parental leave.
• A target bonus and restricted stock units may be included in total compensation, as applicable.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level