Job Description

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.

We just finished YC and are emerging from stealth with $8M in funding from an amazing bench of investors. We're looking for an exceptional AI Engineer who can build our end-to-end sales process and conversion systems from the ground up and drive measurable business outcomes.

You'll create systems that turn traditional insurance sales cycles into efficient, AI-driven processes that improve conversion at every step from lead to binded policy. This role sits at the critical intersection of engineering, AI, and sales—a position to directly impact revenue as we scale from seed to industry leader. You will work directly with the CEO and CTO to shape our sales automation strategy and technical roadmap.

Be bold & aggressive enough to believe we can scale from $1.2M to $100M in run-rate ARR by December.

Outcomes You'll Drive

• Build a Voice AI system that efficiently collects information from customers through natural conversation, capable of sustaining realistic dialogues for a minimum of 15 minutes with complex talk paths and decision trees
• Create product-led experiences where leads can fill out information and track the status of their submitted applications in real-time
• Develop information collection systems that work seamlessly across voice, email, text messages, chat, and product-led forms
• Build recommendation systems that determine which insurance carriers to submit applications to based on customer data
• Create AI agents that manage the back-and-forth communication with customers, collecting required information and documents
• Implement human-in-the-loop escalation paths to Harper operations when complex situations arise
• Develop a lead scoring engine in collaboration with Growth Engineering to prioritize the underwriting queue
• Dramatically improve conversion rates from lead to binded quote through continuous optimization
• Scale our AI-powered sales engine to predictably generate revenue with increasing efficiency

You're Our Person If

• You've built end-to-end systems that improved sales process efficiency and conversion rates
• You're equally comfortable with TypeScript/Node.js and Python/ML frameworks
• You ship features daily and think in terms of weekly experiments, not quarterly plans
• You have a data-driven mindset and can trace your work directly to business metrics
• You've implemented automation systems across multiple channels (voice, email, web)
• You thrive at the intersection of engineering, AI, and sales strategy
• You understand the entire customer journey and know how to optimize each touchpoint
• You can design systems that intelligently route leads through the optimal conversion path
• You're proficient with modern coding environments like Cursor or WindSurf IDE for maximum productivity

Hard Requirements

• Strong experience with both TypeScript/Node.js and Python
• Experience with modern agent orchestration frameworks (Mastra, LangGraph) and Model Context Protocol (MCP)
• Experience building sophisticated voice AI systems capable of sustaining natural conversations for 15+ minutes with complex talk paths
• Experience with multi-channel communication platforms
• Proven track record of implementing systems that directly improved conversion metrics
• Experience with document parsing and information extraction technologies (LlamaParser)
• Familiarity with database design across graph, relational, key-value, and vector stores
• 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 Growth & Data Stack

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

Core Sales Process Technologies:

• Advanced voice AI capable of 15+ minute natural conversations with complex decision trees
• LlamaParser for document parsing and information extraction
• Mastra and LangGraph for AI agent orchestration
• Model Context Protocol (MCP) for LLM interaction management
• OpenAI Function Calling API for web-based agent actions
• LiveKit for real-time voice AI interactions
• Twilio for telephony infrastructure
• OpenPhone for voice transcripts from human conversations
• Human-in-the-loop workflows for complex cases

Memory & Storage:

• Zep AI for graph-based conversation memory
• PostgreSQL for relational memory and structured data
• Redis for high-performance key/value storage
• Vector store with hybrid lexical-semantic search capabilities

Core Engineering:

• TypeScript/Node.js for application development
• Python for AI/ML workflows and data processing
• Temporal workers for distributed compute offloading
• Harper Hub, our operational platform for workflow management and human escalations

Data & Analytics:

• Lead scoring engine for prioritizing opportunities
• Conversion funnel analytics and optimization tools
• A/B testing infrastructure for continuous improvement
• Performance dashboards tied to business metrics

What You'll Build in Your First 90 Days

First Month:

• Build the initial Voice AI system for efficient customer information collection, capable of maintaining natural, engaging conversations for 15+ minutes with complex talk paths
• Create the foundation for a multi-channel information collection system
• Implement document parsing with LlamaParser to extract data from insurance forms
• Set up initial dashboards for monitoring conversion rates at each step of the funnel

Second Month:

• Launch the first version of our customer-facing application tracking portal
• Build AI agents that manage follow-up communications to collect missing information
• Implement the initial insurance carrier recommendation system
• Develop human-in-the-loop workflows for handling complex cases

Third Month:

• Create the lead scoring engine to prioritize the underwriting queue
• Integrate all systems (voice, email, chat, web) into a unified customer experience
• Build comprehensive analytics that identify conversion bottlenecks
• Implement automated optimization systems that improve lead-to-binded-quote conversion
• Deploy your systems to handle real customer interactions with measurable business impact

Sales Process Philosophy

• End-to-End Automation: Build systems that optimize every step from lead to binded policy
• Channel Flexibility: Meet customers where they are through voice, email, chat, or web
• Data-Driven Decisions: Base all sales process improvements on robust analytics
• Human+AI Collaboration: Create effective handoffs between automated systems and human experts
• Experiment Relentlessly: Test hypotheses systematically, scale what works, kill what doesn't
• Revenue Focus: Tie every initiative directly to improved conversion metrics

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 growth teams collaborate intensively in person.

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