Principal Engineer - AI

TCGplayer, an eBay company, is seeking an exceptional Principal Engineer to define and drive their ML/AI technical strategy. This role involves bridging the gap between cutting-edge AI capabilities and practical marketplace applications, focusing on transforming the trading card game marketplace experience using artificial intelligence and machine learning.

Responsibilities:

• Define TCGplayer's multi-year ML/AI technical strategy, identifying transformative opportunities across both customer experiences and internal engineering productivity, with particular focus on practical applications of generative AI
• Design the foundational AI/ML platform architecture that will scale from our current exploratory implementations to production systems serving millions of users, supporting both traditional ML models and LLM-based applications
• Drive adoption of AI-powered development tools and processes, identifying opportunities to accelerate software delivery through code generation, automated testing, intelligent debugging, and documentation assistance
• Design and implement AI-driven operational improvements, from intelligent monitoring and anomaly detection to automated incident response and capacity planning
• Evaluate and prototype emerging AI technologies, particularly in generative AI and LLMs, building proof-of-concepts to validate feasibility and impact before broader investment
• Partner with engineering, product, and data teams to translate business objectives into AI-powered capabilities, starting with intelligent site search and mobile deck-building experiences that may leverage both traditional ML and generative approaches
• Establish AI/ML best practices, including model governance, ethical AI principles, performance benchmarking, prompt engineering standards, and operational excellence for both deterministic and generative systems
• Serve as the technical authority on AI/ML across the organization, educating both leadership and business stakeholders on possibilities and limitations of both established ML techniques and emerging generative AI capabilities
• Drive make-vs-buy-vs-partner decisions for AI infrastructure and capabilities, evaluating vendor solutions, foundation models, and APIs against custom development
• Create technical platform specifications and architecture documents that enable other engineers to implement AI systems aligned with the overall strategy

Requirements:

• 10-12+ years of software engineering experience, with 5+ years specifically architecting and deploying ML/AI systems at scale
• Demonstrated experience setting AI technical strategy and roadmaps in product-driven organizations, with recent focus on integrating generative AI capabilities
• Deep understanding of the full ML lifecycle alongside practical experience with LLM deployment, fine-tuning, and prompt engineering
• Proven ability to communicate complex technical concepts to diverse audiences, from engineers to executives, with clarity and impact
• Track record of evaluating emerging technologies and making pragmatic architectural decisions balancing innovation with delivery, particularly in the rapidly evolving generative AI space
• Experience designing AI platforms that democratize both traditional ML and generative AI capabilities across engineering teams
• Expertise in multiple AI domains (NLP, computer vision, recommendation systems) plus hands-on experience with transformer architectures, RAG systems, and production LLM deployments
• Strong systems thinking with understanding of distributed systems, data pipelines, and production infrastructure for both traditional ML and token-based generative models
• Experience in e-commerce marketplaces, particularly with search relevance, personalization, or fraud detection systems
• Background in building AI applications for mobile platforms with real-time inference requirements, including on-device model deployment
• Knowledge of tabletop gaming or collectibles domains, understanding unique challenges like card recognition, price prediction, or meta-game analysis
• Production experience with RAG systems, semantic search, vector databases, and multi-modal generative AI applications
• Demonstrated ability to evaluate and integrate foundation models (GPT, Claude, Gemini, etc.) into production systems
• Experience with agent-based architectures and autonomous AI systems
• Publications, patents, or conference presentations demonstrating thought leadership in applied AI