Backend Software Engineer, AI Platform

Requirements

• BS in Computer Science, Engineering, or equivalent practical experience.
• 4+ years of software development experience (or equivalent), with a focus on backend or platform engineering.
• Experience building and owning production services (REST/JSON or gRPC) and working in CI/CD environments.
• Experience with at least one cloud or large-scale infrastructure environment.
• Demonstrated experience integrating machine learning or advanced analytics into user- or system-facing products.

Nice to Have

• Experience with decisioning/rules engines, workflow engines, or policy automation platforms.
• Hands-on experience with ML/AI contexts (data pipelines, model training, evaluation, or inference).
• Experience with LLM frameworks (e.g., LangChain, semantic search, RAG) or prior work on AI assistants for internal tools.
• Familiarity with customer service, risk, or trust & safety domains.
• Experience in high-availability, multi-region services and designing for resilience, monitoring, and alerting.

What You'll Be Doing

• Design, implement, and maintain backend services and APIs that power DEX decisioning in both real-time and batch modes.
• Build and integrate ML- and LLM-driven decisioning components (e.g., model inference, feature computation, policy orchestration) into existing rules flows.
• Collaborate with data scientists and rule analysts to productionize models, define interfaces, and deploy decision logic safely at scale (including A/B and canary rollouts).
• Extend our rules and configuration framework so that policy and operations teams can safely author, test, and deploy sophisticated decisions without code changes.
• Partner with product and partner teams (e.g., Customer Support, Risk, Trust, Billing, Returns) to translate business policies into robust, measurable technical solutions.
• Participate in code reviews, architecture discussions, and on-call for the services you own.

Perks and Benefits

• This is an opportunity to shape the next generation of eBay’s decisioning platform, bringing together rules, ML, and LLMs to drive better automation, guidance, and outcomes for customers and teammates.
• Work on a critical, high-visibility system with strong business impact and a team that invests deeply in quality, safety, and innovation.