Staff Software Engineer, AI Systems

Role Overview

We are looking for an Software Engineer, AI Systems to help build the backend architecture behind our emerging agent systems. This role sits at the intersection of software engineering, data infrastructure, and applied AI. You will work across the stack to design and implement systems that power LLM-driven product capabilities — from orchestration and tool integration to evaluation and production deployment. You’ll collaborate closely with product managers, designers, and engineers to bring AI-powered workflows directly into our underwriting platform. This is a high-impact role with significant ownership over both experimentation and production implementation. This role is ideal for engineers who enjoy working across layers of the stack and are excited about shaping how agent systems operate inside real production software.

What You'll Be Doing

• Design and implement agent workflows and orchestration systems for AI-powered product features
• Build backend services that integrate LLMs with structured insurance data and platform APIs
• Develop infrastructure for tooling, context management, and agent execution
• Contribute to internal frameworks supporting prompt iteration, evaluation, and observability
• Partner with product and design to translate underwriting workflows into AI-enabled product experiences
• Help define architectural patterns for building reliable AI-native features in production
• Work across backend systems, data infrastructure, and product integrations to ship user-facing capabilities

Who We Hope You Are

• 10+ years of experience in backend engineering, data engineering, or related roles
• Strong experience building production backend systems and APIs
• Professional experience working with LLMs, agent systems, or generative AI applications
• Hands-on experience with prompt design, tool-based agent architectures, or LLM workflows
• Proficiency in Python or similar backend languages
• Experience working with cloud infrastructure and distributed systems
• Comfort working across layers of the stack, from infrastructure to product integration
• Strong curiosity about emerging AI architectures and agent patterns
• Comfortable navigating ambiguity and working in a fast-paced, collaborative environment

Bonus Points if

• Experience building production systems involving LLMs, agents, or prompt pipelines
• Experience designing internal platforms or developer tooling
• Familiarity with insurance, fintech, or B2B SaaS
• Contributions to open-source AI or data infrastructure projects
• Experience with Types