Lead AI Engineer

Bizee•Houston, TX

About The Position

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. You are building the intelligence layer that powers how entrepreneurs form, manage, and grow their businesses. Real Problems, Real Scale: 50+ state jurisdictions with different rules. Hundreds of thousands of customers. Compliance deadlines that matter. Your AI systems will have measurable business impact. Build the Team: You will inherit a small AI team and grow it. You will define how AI engineering works at Bizee. Your success in building AI capabilities directly drives company valuation. The Role As the Lead AI Engineer, you will build the intelligence layer of Bizee's platform. You will own the AI systems that power personalized recommendations, intelligent automation, and predictive compliance. Your work will directly impact how entrepreneurs experience Bizee: smarter upsells, proactive compliance alerts, and automated document generation. This is a player-coach role. You will lead a team of 3-6 AI/ML engineers while spending 50-60% of your time hands-on: building systems, reviewing code, and shipping features. You report to the Head of Platform and partner closely with Data, Product, and Growth teams. This is a hands-on, 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. We will ask you to show us. Reports to Head of Platform. What You'll Deliver In your first year: Recommendations Engine: Personalized upsell/cross-sell recommendations in production with measurable conversion lift. Compliance Intelligence: AI-powered compliance alerts predicting customer needs before deadlines. Document Automation: Intelligent document generation and extraction reducing manual processing by 50%+. AI Infrastructure: Production-ready AI gateway, model serving, and inference pipelines with cost controls. Team Growth: Grow AI team from 3 to 5-6 engineers. Establish AI engineering practices and code standards. Claude Code Adoption: Champion AI-assisted development across engineering; be the internal expert others learn from. What You Will Own Recommendations & Personalization: Build systems that understand customer context and deliver relevant product suggestions at the right moment. Intelligent Automation: Automate compliance workflows, document processing, and customer communications using LLMs and ML. AI Infrastructure: Model serving, feature stores, inference pipelines, AI gateway, and cost management. LLM Integration: Production LLM applications with guardrails, safety, prompt management, and evaluation. AI Team: Hire, develop, and retain AI/ML engineers. Set technical direction and code standards. What We're Looking For Production AI Experience: 5+ years in software engineering with 2+ years building AI/ML systems in production (not just research or POCs). LLM Application Development: You have built real applications using LLMs (Claude, GPT, etc.). You understand prompting, RAG, fine-tuning tradeoffs, and production deployment. Claude Code Native: You use Claude Code (or similar AI coding tools) daily. It is how you work, not an experiment. Show us what you have built with it. Recommendations/Personalization: Experience building recommendation systems, personalization engines, or similar ML-powered product features. Technical Leadership: You have led small teams (2-5 engineers) or been a strong tech lead. You can mentor, review code, and set technical direction. Full-Stack AI: You can build end-to-end: data pipelines, model training/serving, API integration, and production monitoring. Business Orientation: You measure success by business metrics (conversion, retention, efficiency), not model accuracy alone. What Will Make You Stand Out You can show us production AI applications you have built using Claude Code in the last 6 months. You have built recommendation systems that drove measurable revenue impact. Experience in compliance, legal tech, fintech, or regulatory-heavy industries. You have implemented LLM guardrails, safety systems, and cost management at scale. Background in document processing, OCR, or intelligent automation. You have opinions on AI engineering best practices and can articulate them clearly. This Role Is NOT For You If... You prefer research over production. We ship AI systems, not papers. You have only done traditional ML and have not built with LLMs. You do not use AI coding tools in your daily work. You want a pure IC role with no people leadership responsibility. You optimize for model metrics rather than business outcomes. What We Don't Care About PhD or advanced degrees (show us what you have shipped). FAANG pedigree (show us your production systems). Kaggle rankings or competition wins (show us business impact). Interview Note: We will ask you to show us AI applications you have built, walk through how you use Claude Code daily, and discuss a production AI system you have shipped end-to-end. Come prepared with specific examples and code.

Requirements

5+ years in software engineering with 2+ years building AI/ML systems in production (not just research or POCs).
You have built real applications using LLMs (Claude, GPT, etc.). You understand prompting, RAG, fine-tuning tradeoffs, and production deployment.
You use Claude Code (or similar AI coding tools) daily. It is how you work, not an experiment. Show us what you have built with it.
Experience building recommendation systems, personalization engines, or similar ML-powered product features.
You have led small teams (2-5 engineers) or been a strong tech lead. You can mentor, review code, and set technical direction.
You can build end-to-end: data pipelines, model training/serving, API integration, and production monitoring.
You measure success by business metrics (conversion, retention, efficiency), not model accuracy alone.

Nice To Haves

You can show us production AI applications you have built using Claude Code in the last 6 months.
You have built recommendation systems that drove measurable revenue impact.
Experience in compliance, legal tech, fintech, or regulatory-heavy industries.
You have implemented LLM guardrails, safety systems, and cost management at scale.
Background in document processing, OCR, or intelligent automation.
You have opinions on AI engineering best practices and can articulate them clearly.

Responsibilities

Build systems that understand customer context and deliver relevant product suggestions at the right moment.
Automate compliance workflows, document processing, and customer communications using LLMs and ML.
Model serving, feature stores, inference pipelines, AI gateway, and cost management.
Production LLM applications with guardrails, safety, prompt management, and evaluation.
Hire, develop, and retain AI/ML engineers. Set technical direction and code standards.