Product Engineer – Full Stack

Description

• Triage, diagnose, and ship fixes for incoming platform tickets from Shared Services • Identify recurring friction and systemic platform gaps, then fix them at the source • Own features end to end, including problem framing, design, backend, frontend, instrumentation, rollout, and follow-up fixes • Collaborate with founders, product, and design from the whiteboard stage • Build AI product surfaces, including prompt and agent architecture, tool calling, retrieval, guardrails, and human-in-the-loop escape hatches • Build and maintain evaluation suites and regression tests for AI systems • Analyze session replays, logs, transcripts, support tickets, and customer calls, converting insights into shipped changes • Own latency budgets, token costs, empty states, error copy, loading behavior, and keyboard paths • Cut scope and challenge features before implementation • Improve team velocity through CI, preview environments, internal tools, seed data, and debugging surfaces • Follow product, design, and standard code review processes • Participate in weekly syncs with Engineering, Operations, and Product

Requirements

• 4+ years of full stack software engineering experience shipping production enterprise software • Direct experience building internal tools, agent-facing platforms, or operational systems • Product mindset: comfortable scoping problems, asking the right questions, and communicating/prioritizing tradeoffs • Track record of shipping fast while working inside a product and design process • Experience working asynchronously with distributed teams • Strong fluency in TypeScript • Experience with Next JS, NestJS, TypeORM with Postgres, and BullMQ • Comfortable with agentic coding tools (Claude Code, Cursor, Replit Agent) • API integration experience (REST, webhooks, third-party SaaS APIs) • Prompt engineering experience with production AI systems (OpenAI, Anthropic, or similar) • 5 hours of overlap with Miami time (Eastern), minimum, daily • Strongly preferred: experience building tools for contact center, customer support, or operations teams • Strongly preferred: short-term rental, hospitality, or property management domain knowledge • Strongly preferred: track record of deploying AI agents in production

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