We are seeking a highly accountable, hands-on AI Lead Engineer to define and lead the architectural direction of our AI services, establishing the standards and patterns that guide implementation. As a key member of the AI technical staff, you will shape the architecture, design standards, and implementation approach for production-grade AI systems that power critical business capabilities. You will partner closely with Product and Engineering leadership to translate business objectives into scalable, well-architected AI solutions. This role combines deep hands-on development with architectural leadership: setting technical patterns, guiding major initiatives from design through delivery, and ensuring our AI services are reliable, performant, and cost-aware in production. What You'll Do: - 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 How You’ll Work - 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 Who You Are: - 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 Nice to Have - 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) What Success Looks Like - AI initiatives ship with strong architectural integrity and measurable business impact - AI services are scalable, reliable, and cost-aware in production - Clear architectural direction is reflected in design decisions and implementation standards - Senior Engineers grow in capability through mentorship and architectural guidance - Cross-functional collaboration results in well-aligned, well-executed AI solutions #LI-LH1 #LI-REMOTE (Pay Transparency Range: $163,040 - $244,560) Compensation Transparency The national base salary range for this role is posted above in this job post. Final compensation will be determined based on factors such as relevant experience, skills, qualifications and geographic location. We also consider internal equity to help ensure fair and consistent pay practices across our teams. Where applicable, this role may also be eligible for variable compensation (such as bonus or commission), equity, and benefits in accordance with local policies. Details will be shared during the hiring process. We are committed to equitable and transparent pay practices that align to market data, internal equity, and individual contribution.