AI Platform Engineer

Overview

The Mission

We\'re building an AI-powered insurance brokerage that is transforming the $900 billion commercial insurance market by automating processes that currently run on pre-internet systems. Fresh off our $8M seed round, we\'re looking for an exceptional AI Platform Engineer who can architect and develop the core infrastructure that powers our entire AI ecosystem.

You\'ll build the foundational platform that enables our AI agents to operate across growth, sales, operations, and customer service. This includes extending our proprietary AI Grid context engineering system, developing evaluation infrastructure, building ML models for market-making and reasoning, and creating the systems that enable massive operational leverage (enabling one person to do the work of thousands). You\'ll be responsible for both ambient agents (background processes with context / memory) and the core systems that enable frontier agents (human-AI interfaces) to deliver exceptional experiences.

We\'re committed to "Staying REAL" with our AI systems - building agents that are Reliable, Experience-focused, Accurate, and have Low latency. You will work directly with the CEO and CTO to execute on our AI vision with a bias toward action. We live by core principles : "There is no try, there is just do," "Actions lead to information, always default to action," and "Strong opinions lead to information." We need engineers who build and ship, not just plan and strategize.

Responsibilities / What You\'ll Do

• Extend and enhance our proprietary AI Grid context engineering system that combines ETL with LLM pipelines and graphs
• Build robust evaluation systems with datasets and human-annotated data for supervised fine-tuning (SFT) and reinforcement learning (RL)
• Develop ML models for critical systems including underwriter load balancing (our market-making engine) and reasoning systems
• Architect and maintain data pipelines that pull from multiple diverse sources and push to various destination systems (ClickHouse, vector databases, ML platforms, etc.)
• Build MCP (Model Context Protocol) servers that expose memory and tools to AI agents across the platform
• Create integrations with payment providers and financial systems for seamless transaction processing
• Develop growth engineering infrastructure including agents that determine campaign strategies and optimize outreach
• Build voice AI systems for follow-ups, information collection, and cold outbound campaigns
• Create customer service AI infrastructure enabling one person to manage thousands of leads and customers
• Design ETL / ELT pipelines that handle both batch and real-time processing at scale
• Implement Lambda architecture patterns combining event streaming with batch processing
• Partner with forward deployed engineers to ensure platform capabilities meet business needs
• Build comprehensive observability systems to monitor agent reliability and performance

You're Our Person If

Hard Requirements

Our Tech Stack

AI Agent Infrastructure

Data & ML Infrastructure

Core Engineering

What You\'ll Build in Your First 90 Days

First Month

Second Month

Third Month

Our AI Philosophy

Join Us To Transform the $900B Insurance Market

This is an early-stage role at a fast-moving startup, and you\'ll often experience the crawl-walk-run approach to building. You\'ll quickly prototype systems and then push them into productionized platforms that can scale. We\'re looking for people who can be creative in providing impact first, then take learnings from that impact and push them back into the system.

You should ideally have worked in an early-stage startup environment and understand the pacing. This is a fast-paced environment where we value ownership and quick, rapid feedback loops within the team. You\'ll work directly with the CEO and CTO to execute on our AI vision with a bias toward action.

We require you to be in San Francisco and work from our office 5.5 days per week. We\'ll cover relocation costs and believe the best teams collaborate intensively in person.

Skills

TypeScript, Node.js, Python, Distributed Systems, Context Engineering, AI Grid, Data Engineering, Databricks, Astronomer, ETL / ELT, ML Infrastructure, Data Enrichment, DAG Orchestration, Temporal.io, Pydantic-AI, MCP Servers, Evaluation Systems, SFT / RL, Voice AI, Payment Integration, Event Sourcing, CAP Theorem, Lambda Architecture, Apache Airflow, Vector Databases, RAG Systems, Redis Streams, PostgreSQL, AI Agent Development, System Architecture, Market-Making Systems, Reasoning Engines

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