Jobs / United States / Ebay INC
AI Native Software Engineer, Risk
Ebay INC · 🇺🇸 Austin
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 478 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 314 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Ebay INC paid sponsored hires in similar roles58 certified filings for “MTS 1, Software Engineer” (Software Developers) in TX: $142k–$188k, median $169k. Most were filed at wage level IV (58%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Ebay INC
The US Department of Labor certified 478 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 314 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Ebay INC →
About the role
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. About the Team Global Payments and Risk builds products and platforms that enable safer, more trusted commerce experiences. We use data, modern software architectures, and AI-native engineering practices to solve risk challenges at scale across detection, decisioning, automation, and operational workflows. This team operates highly scalable systems with meaningful customer and business impact. Job Summary We are seeking a talented Software Engineer to build and operate the platforms and services that enable smarter risk decisions, seamless automation, and resilient workflows at scale. In this hands-on role, you will deliver scalable, reliable, and secure software systems that drive meaningful business impact across Risk Engineering . Engineers in this organization are expected to use modern AI-enabled practices effectively. In this role, that includes applying AI where it can improve product quality, operational efficiency, and engineering productivity. This is a hands-on, applied software engineering role with end-to-end ownership for builders who want to design, ship, and operate real systems in production. What You Will Do • Design, build, test, deploy, and support production-ready AI-enabled systems that solve real customer and business problems in Risk Engineering. • Build end-to-end services and workflows that combine LLMs, retrieval, tool use, structured outputs, deterministic logic, and human review where appropriate. • Develop scalable backend services, APIs, and integrations that support risk decisioning, investigation, and automation use cases. • Translate business and operational needs into clear 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 bars for AI behavior through task-level evaluations, offline and online metrics, regression detection, and release criteria. • Improve reliability, scalability, latency, security, and cost efficiency of AI-enabled systems in production. • 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 high-quality code, design documents, and test plans, and raise engineering standards through thoughtful reviews and documentation. Minimum Qualifications • Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. • 4+ years of software engineering experience building and operating production systems. • Strong proficiency in at least one backend language such as Python, Java, TypeScript. • Experience building and shipping backend services or product features, including design, implementation, testing, launch, and production support. • Experience building with modern AI capabilities in production or at meaningful scale, such as LLM-based workflows, tool calling, ret