Lead Software Engineer - AI

Commerce is an AI-driven commerce technology company that helps businesses solve complex commerce challenges through connected tools, systems, and data. The Lead Software Engineer - AI will define architectural direction for AI services, build production-grade AI systems, and guide major initiatives from design through delivery while ensuring scalability, reliability, performance, and cost awareness.

Responsibilities:

• Define and evolve the architectural direction for AI services and initiatives
• Lead high-level and low-level design for major AI programs
• Establish architectural patterns and technical guidelines that other engineers follow
• Build and evolve scalable, API-driven AI services in Go
• Develop LLM-based solutions, including classification, extraction, structured generation, and RAG workflows
• Drive rapid experimentation and prototyping (often in Python), ensuring clear paths to production-ready implementations
• Define and enforce standards for evaluation, cost-awareness, and operational reliability across AI systems
• Mentor Senior AI Engineers through design reviews and technical guidance
• Collaborate with Staff Engineers when broader architectural alignment is required
• Work directly with Product Managers and stakeholders to clarify goals and define measurable success criteria
• Balance hands-on engineering with architectural oversight
• Ensure architectural consistency and adherence to established design standards
• Raise the technical bar through thoughtful reviews and shared engineering standards

Requirements:

• 7+ years of professional software engineering experience
• Strong proficiency in Go (GoLang) and experience building production-grade, API-driven services
• Proficiency in Python for experimentation, prototyping, and scripting
• 3+ years of experience building and deploying AI/ML systems in production environments
• Strong experience with modern LLM ecosystems (e.g., OpenAI, Anthropic, Hugging Face)
• Deep understanding of LLM-based solution patterns, including Retrieval-Augmented Generation (RAG), structured outputs, schema-driven generation, and agents/orchestration workflows
• Familiarity with MCP (Model Context Protocol) servers and orchestration approaches
• Experience evaluating LLM performance in production contexts, including prompt design, quality measurement, and model comparison
• Experience designing and operating scalable API services at scale
• Strong experience with cloud infrastructure (AWS, GCP, or Azure)
• Experience with vector databases and inference systems
• Strong SQL skills and familiarity with modern data storage technologies
• Experience working with large taxonomies or structured classification systems
• Experience in e-commerce, product catalogs, or sales channel data models
• Familiarity with frontend frameworks (React, Angular)