The Mission

We're building an AI-powered insurance brokerage that's 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 Applied AI Engineer who can architect and develop intelligent agent systems across our entire customer journey.

You'll create sophisticated AI systems that turn traditional insurance processes into efficient, data-driven experiences powered by both ambient and frontier AI agents. Ambient agents will work continuously in the background, hooking into context and memory, while frontier agents will serve as the critical interface between ambient agents and human operators - delivering low-latency, high-quality collaboration experiences. This role sits at the critical intersection of engineering, AI, and business operations—a position to directly shape how we scale from seed to industry leader.

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.

Outcomes You'll Drive

• Design and implement AI agent architectures using temporal.io workflows and pydantic-ai, adhering to distributed systems best practices
• Develop deep understanding of CAP theorem tradeoffs between Consistency, Availability, and Partition tolerance to build resilient agent systems
• Implement Lambda architecture patterns combining event streaming for real-time processing with batch processing for comprehensive analytics
• Design and develop frontier agents that provide exceptional human-AI collaboration interfaces with low latency and high accuracy
• Create ambient agents working in background processes that connect seamlessly to frontier agents for a unified system
• Build sophisticated voice AI systems for frontier agents that facilitate natural, contextually rich conversations with customers
• Build highly Reliable ambient agents that monitor event streams and proactively take action based on triggers, with robust recovery mechanisms and fault tolerance
• Architect communication protocols between ambient agents and frontier agents to ensure seamless information flow
• Build retrievers and RAG systems that instantly surface relevant policy information and domain knowledge with high Accuracy during interactions
• Develop self-service flows for customer onboarding and policy management that maximize conversion and deliver superior user Experience
• Architect human-in-the-loop workflows that smoothly transition between AI and human experts with minimal Latency
• Design comprehensive observability with logfire to monitor agent Reliability, performance, and outcomes
• Establish rigorous evaluation frameworks to continuously improve agent Accuracy and optimize conversion rates

You're Our Person If

• You're experienced with our REAL framework for building reliable, experience-focused, accurate, and low-latency AI systems
• You have deep expertise with distributed systems, event sourcing, and scalable architecture patterns
• You understand CAP theorem tradeoffs and can make appropriate architectural decisions for different system requirements
• You can implement Lambda architecture combining real-time event processing with batch analytics pipelines
• You're equally comfortable with TypeScript/Node.js and Python/ML frameworks
• You're proficient with modern agent orchestration frameworks and temporal.io workflows
• You ship features daily and take immediate action instead of overthinking
• You embrace "there is no try, there is just do" as your engineering mantra
• You understand that actions lead to information, and default to shipping code
• You hold strong opinions but remain open to learning from real-world results
• You're a pro at using AI coding assistants like Cursor or WindSurf to accelerate development
• You excel at delegating logic to AI to achieve outcomes while maintaining oversight
• You thrive at the intersection of engineering, data, AI, and business strategy

Hard Requirements

• Strong experience with both TypeScript/Node.js and Python
• Experience with temporal.io workflows and pydantic-ai for building durable agent systems
• Deep understanding of distributed systems principles, CAP theorem tradeoffs, and event sourcing architecture
• Experience designing systems that balance consistency, availability and partition tolerance based on specific use cases
• Proficiency in implementing Lambda architecture with both real-time event streaming and batch processing
• Proven track record building sophisticated voice AI or multi-channel communication systems
• Experience with multi-channel communication platforms (voice, email, chat, web)
• Strong frontend development skills with Next.js/React
• Proven ability to implement systems that directly improved business metrics
• Advanced usage of Cursor or WindSurf coding IDE
• Must be based in San Francisco and work in-office 5.5 days per week (relocation assistance provided)

Our Tech Stack

We're building a modern, AI-native infrastructure to power our growth:

AI Agent Infrastructure:

• Temporal.io for durable workflow orchestration across agent systems (for Reliability)
• Pydantic-AI for type-safe agent development with structured validation (for Accuracy)
• Event sourcing architecture with Redis streams and PostgreSQL (for Reliability)
• Lambda architecture combining real-time event streams and batch processing
• RAG systems with rigorous evaluation frameworks for domain-specific knowledge (for Accuracy)
• Optimized response processing for minimal user waiting times (for Latency)
• Claude (Anthropic), GPT-4.1 (OpenAI), and select open source models
• Model Context Protocol (MCP) for optimized LLM interactions (for Latency)
• Logfire for comprehensive agent observability and analytics (for the entire REAL framework)
• User-centered design principles for intuitive agent interactions (for Experience)

Voice & Conversational Systems:

• LiveKit for real-time, bidirectional voice communication
• Twilio for enterprise-grade telephony infrastructure
• OpenPhone for capturing and analyzing human conversations

Core Engineering:

• TypeScript/Node.js for robust application development
• Python for AI systems and ML workflows
• Next.js/React for frontend experiences and customer portals
• Temporal workers for distributed, fault-tolerant process execution
• Event-driven architecture with Redis streams for scalable applications

Memory & Storage:

• Event sourcing with PostgreSQL for transactional data
• Redis for high-performance caching and messaging
• Vector databases for semantic search capabilities

What You'll Build in Your First 90 Days

First Month:

• Build and deploy outreach agent underwriter submission load balancer that manages quoting across human underwriters and online portals
• Design and implement the core architecture for ambient agents using temporal.io and pydantic-ai
• Create voice AI system capable of handling basic insurance inquiries with low latency and high reliability
• Set up comprehensive observability with logfire to implement the REAL framework metrics
• Create dashboards that provide real-time visibility into user experience quality and agent accuracy

Second Month:

• Develop graphs of agents via temporal and pydantic-ai to handle complex insurance workflows
• Build customer service agents specialized for policy renewals and claims processing
• Design intelligent escalation paths that seamlessly transition from AI to human experts
• Implement AI forms and voice AI to collect information via product-led growth channels
• Create outreach AI agents that nurture leads through personalized outbound campaigns

Third Month:

• Develop autonomous feedback loops where conversion and satisfaction data improves targeting
• Build personalization engines that adapt messaging based on prospect characteristics
• Implement comprehensive analytics that identify conversion bottlenecks
• Scale AI agents for end-to-end automation of key insurance processes
• Integrate all agent systems into a unified, observable architecture with logfire

Our AI Philosophy

1. Staying REAL: Our framework for building AI agents that are:
   • Reliable: Agents that consistently perform, handle edge cases, and recover gracefully from failures
   • Experience-focused: Creating intuitive, natural interfaces for human-AI interaction
   • Accurate: Ensuring high-quality outputs through rigorous evaluation frameworks and feedback loops
   • Low latency: Delivering smooth, responsive interactions that feel conversational and immediate
2. Ambient + Frontier Agents Architecture: Build a two-tier agent system where ambient agents work continuously in the background handling routine tasks, while frontier agents provide the human-AI collaboration layer with low-latency, excellent experience and accurate communication between systems
3. Event-Driven Architecture: Design systems that react to events and state changes for maximum responsiveness
4. Distributed & Durable: Create fault-tolerant agents that maintain state and recover from failures
5. CAP Theorem Understanding: Make intelligent tradeoffs between consistency, availability, and partition tolerance based on specific use cases
6. Lambda Architecture Approach: Combine event streaming for real-time processing with batch processing for complete analytics
7. Action Orientation: Always default to action - ship code, gather data, and iterate rather than overthink or overplan
8. Execution Focus: There is no try, there is just do - we value engineers who build and ship, not just plan and strategize
9. Strong Opinions: Form and express clear viewpoints that can be tested against reality to generate valuable information
10. Revenue Focus: Tie every initiative directly to business outcomes and improved metrics

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 applications and then push them into productionized systems 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, Temporal.io, Pydantic-AI, Event Sourcing, Distributed Systems, CAP Theorem, Lambda Architecture, Next.js/React, Model Context Protocol, RAG Systems, Voice AI, Vector Databases, Redis Streams, PostgreSQL, Full-Stack Development