Harper (YC W25) · 5 months ago
AI Platform Engineer
San Francisco, CA
Full-time
Onsite
Mid Level
$140K/yr - $230K/yrHarper is an innovative startup building an AI-powered insurance brokerage aimed at transforming the commercial insurance market. They are seeking an exceptional AI Platform Engineer to architect and develop the core infrastructure for their AI ecosystem, including building ML models and enhancing their proprietary AI Grid system.
Artificial Intelligence (AI)FinTechInsurance
Responsibilities
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
Qualification
Required
Strong experience with both TypeScript/Node.js and Python
Deep understanding of distributed systems principles, CAP theorem tradeoffs, and event sourcing architecture
Experience with modern data warehouse solutions (Databricks, Astronomer, Snowflake, or similar)
Proven track record building ML modeling infrastructure and ETL/ELT pipelines
Experience with evaluation systems and human-annotated datasets for ML training
Experience building ML models for complex systems (recommendation engines, market-making, reasoning)
Experience with MCP server architecture and protocol implementation
Experience with voice AI systems and conversational interfaces
Experience with payment provider integrations and financial systems
Experience designing data pipelines that serve multiple destination systems
Experience with temporal.io workflows or similar durable execution frameworks
Experience with data enrichment and DAG-based orchestration
Proven track record building production AI/ML systems at scale
Experience with vector databases (Qdrant, Pinecone, Weaviate) and RAG systems
Strong understanding of context engineering for AI systems
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)
Preferred
You're exceptional at one or more of: distributed systems, AI agents, context engineering, or data engineering
You have experience building evaluation systems and working with human-annotated datasets for ML training
You understand how to build ML models for complex systems like market-making and reasoning engines
You have deep expertise with modern data warehouse and ML platforms (Databricks, Astronomer, or similar)
You can architect MCP servers and understand how to expose memory and tools to AI systems
You have experience with payment provider integrations and financial systems
You understand how to build voice AI infrastructure for outbound campaigns and information collection
You can architect systems that enable massive operational leverage (1:1000s ratios)
You have experience with data enrichment and building DAG-based orchestration systems
You understand CAP theorem tradeoffs and can make appropriate architectural decisions
You're equally comfortable with TypeScript/Node.js and Python/ML frameworks
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
Benefits
Relocation assistance provided
Company
Harper (YC W25)
Harper is a commercial E&S insurance brokerage.
Founded in 2024
2-10 employees
Funding
Current Stage
Early StageTotal Funding
$0.5MKey Investors
Y Combinator
2025-03-12Pre Seed· $0.5M
Company data provided by crunchbase