At e Bay, 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 role & team

The Agentic Systems Research team is responsible for advancing the scientific foundations and practical deployment of AI agents operating within e Bay’s global marketplace.

We are building systems that combine large language models, retrieval systems, recommender models, and structured marketplace knowledge to create agents that can reason, plan, and take actions across complex commerce workflows.

As a Principal Applied Researcher, you will play a central role in shaping e Bay’s research agenda in Generative AI and agentic systems. You will lead high-impact applied research initiatives that push the boundaries of what AI agents can accomplish in real-world environments while delivering measurable improvements to e Bay’s buyer and seller experiences.

This is a senior individual contributor role focused on technical leadership, research direction, and delivering production impact at scale.

What you will accomplish

• Define and drive research initiatives in agentic AI systems, including architectures for planning, tool use, workflow orchestration, and long-horizon reasoning.

• Lead the development of next-generation AI systems that combine LLMs, retrieval systems, recommender models, and structured marketplace data to support complex buyer and seller workflows.

• Develop methods to make agentic systems reliable, controllable, and measurable when deployed in large-scale real-world environments.

• Design and advance evaluation methodologies for agentic AI, including trajectory evaluation, human-in-the-loop evaluation, safety testing, and online experimentation.

• Translate research insights into production systems by partnering closely with engineering and product teams.

• Influence technical strategy and roadmap decisions through strong technical judgment and data-driven insights.

• Mentor researchers and engineers, contribute to technical reviews, and raise the overall research and engineering bar across the organization.

• Represent e Bay’s AI research efforts through publications, patents, and engagement with the broader research community.

What you will bring

Education:

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a closely related field strongly preferred.

• A Master’s degree with significant applied research experience may also be considered.

Deep Technical Expertise:

• Strong expertise in modern AI systems, particularly in areas such as: Large Language Models and generative AI, Natural language understanding and reasoning, Retrieval systems and information retrieval, Recommender systems and personalization, Representation learning etc.

• Experience designing and deploying large-scale machine learning systems in production environments.

• Strong programming skills in Python and distributed computing environments such as Spark or similar systems.

Agentic Systems Experience

Hands-on experience designing or working with agentic AI architectures, such as:

• Tool-using LLMs

• Multi-step reasoning and planning systems

• Workflow orchestration frameworks

• Memory and state management for agents

• Agent reliability, guardrails, and safety systems

• Experience building systems that integrate LLMs with structured APIs, knowledge sources, or enterprise data systems.

Research Leadership

• Proven ability to lead applied research initiatives end-to-end, including: problem formulation, hypothesis development, experimental design, evaluation methodology development, production integration, etc.

• Track record of delivering machine learning innovations that have measurable product impact.

• Experience defining success metrics and designing evaluation frameworks to guide research investment.

Collaboration & Influence

• Excellent collaboration and communication skills, with the ability to work effectively across research, engineering, and product organizations.

• Ability to influence technical direction and decisions across teams without formal authority.

Additional Details

e Bay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at talent@ebay.com. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about e Bay's commitment to ensuring digital accessibility for people with disabilities.

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