Director Customer Experience Engineering

eBay•Bellevue, WA

17h•Hybrid

About The Position

This role is part of the Global Platforms team in Customer Service Technology at eBay. The group builds foundational systems, services, and smart capabilities that support customer interactions at scale across eBay. The team plays a significant role in unifying fragmented experiences and ensuring consistent, high-quality engagement across all customer touchpoints. We are looking for a Director Customer Experience Engineering to guide this transformation in close collaboration with product, development, and business leadership.

Requirements

15+ years of software engineering experience, with 5 or more years in people management and 3 or more years managing managers.
Proven experience leading large-scale customer-facing platforms, ideally including support or service experiences.
Strong technical background in distributed systems, AI or machine learning-enabled platforms, or intelligent automation systems.
Experience building or scaling conversational systems, decisioning platforms, or automated workflows.
Ability to translate business and customer experience strategy into intelligent, scalable engineering solutions.
Track record of delivering complex, high-quality systems at scale with measurable customer impact.

Nice To Haves

Experience in ecommerce, marketplace, or consumer platforms.
Background in customer support technologies, automation, or service platforms.
Experience working with large language models, conversational AI, or recommendation systems in production environments.
Experience driving AI-first or automation-first transformation initiatives.
Proven success scaling teams through platform modernization and organizational change.

Responsibilities

Define and drive the technical vision and roadmap for customer experience transformation across the platform.
Lead the evolution toward agentic customer experiences where intelligent systems identify issues, recommend actions, and resolve customer needs end to end.
Translate business and customer experience strategy into scalable engineering solutions that improve end-to-end customer journeys, especially during moments of friction or support need.
Partner closely with Product, Design, and customer experience leadership, to align on north star metrics such as NPS, resolution time, containment, conversion, and trust.
Champion a customer-first and AI-first engineering approach, ensuring all systems are grounded in user impact and measurable outcomes.
Build and scale platforms that enable intelligent, context-aware assistance, including: Conversational interfaces and orchestration layers, Decisioning systems for next-best action and automated resolution, Knowledge systems that power dynamic, real-time responses.
Drive the development of autonomous workflows that resolve common and complex customer issues without manual intervention.
Enable human-in-the-loop systems that augment support agents with real-time insights, recommendations, and automation.
Partner with Data Science and AI teams to productionize machine learning and large language model capabilities in a safe, scalable, and reliable manner.
Ensure strong governance around trust, safety, privacy, and explainability in all intelligent systems.
Lead, mentor, and scale a high-performing organization of Engineering Managers and senior engineers.
Build capabilities in AI and machine learning engineering, distributed systems, and platform development within the team.
Foster a culture of innovation, experimentation, and responsible AI development.
Attract and retain top talent aligned with the transformation vision.
Oversee execution of complex, multi-functional initiatives spanning customer experience and intelligent support systems.
Deliver scalable platforms that support high-volume, real-time customer interactions.
Ensure engineering excellence across availability, latency, and system reliability, especially in customer-critical flows.
Drive measurable improvements in resolution speed, containment rates, and customer satisfaction.
Establish processes to support rapid experimentation and iteration of features powered by artificial intelligence.
Implement observability and feedback loops to continuously improve model performance and system outcomes.
Define and track key performance indicators tied to both engineering health and customer experience outcomes.
Lead incident response and continuous improvement practices for customer-facing systems.
Partner deeply with Product, Design, Data Science, Trust, and Operations to deliver cohesive, intelligent customer experiences.
Collaborate with senior leadership to prioritize investments in automation, intelligence, and platform unification.
Serve as a key leader in crafting how the organization adopts and scales customer experiences powered by artificial intelligence.
Ensure all systems meet the highest standards for trust, safety, and privacy, especially in automated decision-making.
Establish safeguards and critical issue paths for edge cases and sensitive customer scenarios.
Champion transparent and explainable systems that build customer confidence in automated experiences.