Principal Software Engineer, AI

Role Overview

What You'll Do

What We're Looking For

What We Offer

• Competitive salary and meaningful equity in a high-growth company
• 100% company-paid base medical, dental, and vision coverage for employees + healthcare FSA
• 401(k) savings plan
• Unlimited PTO and paid family leave
• Home office & equipment stipend
• Daily in-office lunch and dinner provided
• Commuter benefits (pre-tax transit and parking)
• PermitFlow provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, gender expression, or family status, as protected by applicable law.
• We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities. All employment decisions are based on merit, qualifications, and business needs.

Qualifications

• You've shipped an assistant or agentic product at meaningful scale
• Deep, current knowledge of the agentic stack (tool calling and tool design, context engineering, memory, retrieval, orchestration patterns, etc)
• You’ve built eval harnesses that changed what a team worked on, and you can articulate what makes an eval trustworthy.
• You are a genuinely strong software engineer, not an AI specialist who needs someone else to make it production-ready. You’ve owned services in production and you write code that other people are glad to inherit.
• You operate with earned authority. You influence through demonstrated judgment, working code, and clear writing rather than title or mandate.
• 10+ years of software engineering experience with recent time spent building LLM-powered products.

Responsibilities

• Own the agent architecture. Design the reasoning loop, planning and decomposition strategy, state and session model, and recovery behavior for long-running tasks.
• Build the context layer. Retrieval, memory, and context-window management over project documents, jurisdictional requirements, prior submissions, and customer-specific conventions.
• Design the action surface. Define the tools the assistant can call, the permissions model around them, and the human-in-the-loop checkpoints for actions that are expensive or irreversible.
• Make evaluation the engine of progress. Stand up offline and online eval harnesses that measure task completion and failure modes. Build the iteration loop that lets the whole team improve agent quality on evidence.
• Set the bar for the org. Establish the abstractions, SDKs, and review standards other engineers build agentic features on.
• Stay close to the customer. Sit with permit coordinators and builders, watch the assistant fail in real conditions, and bring that back into the system design.
• You've shipped an assistant or agentic product at meaningful scale
• Deep, current knowledge of the agentic stack (tool calling and tool design, context engineering, memory, retrieval, orchestration patterns, etc)
• You’ve built eval harnesses that changed what a team worked on, and you can articulate what makes an eval trustworthy.
• You are a genuinely strong software engineer, not an AI specialist who needs someone else to make it production-ready. You’ve owned services in production and you write code that other people are glad to inherit.
• You operate with earned authority. You influence through demonstrated judgment, working code, and clear writing rather than title or mandate.
• 10+ years of software engineering experience with recent time spent building LLM-powered products.