Sr AI Engineer

About the role

We are seeking a highly skilled Senior AI Engineer to design and implement advanced agentic AI systems. In this role, you'll build production-ready AI agents that can reason across multiple steps. You'll work with state-of-the-art frameworks to create pipelines that combine LLM-based reasoning, knowledge grounding, and multi-agent orchestration.

Responsibilities

• Build Agentic Systems – Implement multi-step reasoning agents. Retrieval-Augmented Generation (RAG), and integrations to tools, databases, and APIs.
• Orchestrate & Optimize – Design supervisor/sub-agent patterns, enable coordination across agents, and apply best practices for robustness, performance, and scalability.
• Deploy & Evolve – Deliver production-grade agentic AI workflows on cloud platforms, monitor and evaluate agent performance, and continuously fine-tune for quality and efficiency.
• Develop scalable services that connect with multiple eBay systems, establishing standards for reliability, and operational excellence.

Requirements

• Hands-on experience with multi-agent orchestration and supervisor patterns.
• Knowledge of RAG pipelines, memory management, and evaluation of agent performance.
• Experience designing custom evaluation metrics for reasoning steps, tool use correctness, and RAG pipeline performance.
• Ability to balance automatic evaluation with human-in-the-loop evaluation for complex workflows.
• Proficiency in Python and familiarity with backend cloud services.
• Proficiency in developing backend services using Java (Spring / Spring Boot).
• Experience with agentic architecture, including agent frameworks, tool-calling protocols, and planning/execution patterns.
• Knowledge of reinforcement learning, planning algorithms, or autonomous reasoning.

Qualifications

• 6+ years of hands-on experience in developing RESTful APIs, microservices, and Kubernetes operators, with an emphasis on testability, scalability, and maintainability.
• Proven experience leading and contributing hands-on to AI/ML engineering and operations in large-scale production environments.
• Deep understanding of AI model lifecycle management, distributed systems, and integration of applications powered by artificial intelligence into customer-facing platforms.
• Develop and maintain highly scalable, efficient, performant & resilient capabilities, meeting availability targets of 99.99%.