About Bizee Bizee (formerly Incfile) has helped over 1 million entrepreneurs start and run their businesses. We are transforming from a transaction-focused formation business to an AI-powered operating system for entrepreneurs. We champion the everyday entrepreneur. We believe in self-determination, grit, and earned success. No fluff, no jargon, no pretense. We work hard, ship fast, and let our products speak for themselves. What Makes Working Here Different - AI is the Product, Not a Feature: You are not building AI for a demo or bolting a chatbot onto an existing product. You are building the shared intelligence layer that every product squad at Bizee consumes to deliver smarter experiences to entrepreneurs. - Platform That Multiplies: Your work is a force multiplier. When you ship a capability, such as a model serving pipeline, an evaluation framework, or a cost-optimized inference layer, every squad across the organization builds on it. Your leverage is measured by how much faster other teams ship AI-powered features because of what you built. - Real Problems, Real Scale: 50-state jurisdictions with different rules. Hundreds of thousands of customers. Compliance deadlines that matter. The AI systems you build will power decisions at scale with real business consequences. - Craft Matters Here: We care about production-grade AI systems with proper guardrails, cost controls, and observability, not impressive demos that break in production. Your squad sets the quality standard for how AI is built at Bizee. The Role As the Technical Lead, AI Platform, you lead the squad that builds and operates Bizee's shared AI infrastructure. Your team provides the foundational capabilities that product squads use to ship AI-powered features: model serving, LLM integration, inference pipelines, AI gateway, guardrails, evaluation frameworks, and cost management. You own is the infrastructure, tooling, and shared services that make all of that possible, reliable, and cost-effective. Your success is measured by how effectively product squads can build and ship AI capabilities on top of what your team provides. This is a building role with leadership responsibilities. You spend 60%+ of your time writing production code, building infrastructure, and reviewing PRs. The rest goes to squad coordination, cross-squad support, and technical mentorship. If your approach is to "coordinate and delegate," this is not the right fit. You are the strongest AI engineer on the team, and you prove it every sprint. This is an AI-native engineering role. You live in Claude Code. You ship production AI systems, not prototypes. You can demonstrate real applications you have built using LLMs, not just fine-tuning experiments. You are the internal expert that other engineers learn from when they need to integrate AI capabilities into their domains. We will ask you to demonstrate this with real examples. Reports to Head of Platform Engineering. Works closely with Principal Engineer, Data & Analytics, and product squad Technical Leads on AI integration patterns and shared capabilities. What You Will Deliver In your first 6-12 months: - AI Gateway and Inference Layer: Production-ready AI gateway with model routing, rate limiting, cost controls, and observability. Product squads can call AI capabilities through a clean, well-documented interface without managing model infrastructure directly. - LLM Integration Framework: Shared LLM application layer with prompt management, versioning, guardrails, safety controls, and evaluation pipelines. Reduce the time for any product squad to ship a new LLM-powered feature from weeks to days. - Model Serving Infrastructure: Scalable model serving pipeline supporting both real-time inference and batch processing. Cost-optimized for Bizee's traffic patterns with clear cost attribution by squad and feature. - Evaluation and Quality Framework: Automated evaluation pipelines for LLM outputs, recommendation quality, and AI system reliability. Product squads can measure and iterate on their AI features with confidence, not guesswork. - AI Developer Experience: Documentation, examples, and patterns that make it easy for any engineer at Bizee to integrate AI capabilities into their domain. Champion AI-assisted development (Claude Code) across engineering. Be the internal expert others learn from. - Squad Delivery: 85%+ sprint commitment rate. Weekly releases with zero rollbacks caused by preventable quality issues. - Team Growth: Grow the AI platform squad to 3-4 focused engineers. Establish AI engineering practices, code standards, and on-call rotation for AI infrastructure. What You Will Own - AI Gateway: Centralized AI service layer including model routing, authentication, rate limiting, cost management, and usage tracking across all product squads. - LLM Application Layer: Shared prompt management, retrieval-augmented generation (RAG) infrastructure, guardrails, safety systems, and output evaluation. - Model Serving: Inference pipelines, model deployment, A/B testing infrastructure for model variants, and real-time vs. batch serving capabilities. - AI Observability: Monitoring, alerting, cost dashboards, and performance tracking for all AI systems in production. You know what is running, what it costs, and how well it is performing at all times. - AI Platform Squad: Hire, develop, and retain AI platform engineers. Set technical direction, code standards, and engineering culture for the squad.