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Confidential

Senior Product Engineer · 💰 $130,000 – $200,000

North America

October 7, 2026 at 3:23 AM

✨ AI summary

💰 $130,000 – $200,000

Location

  • East Coast US preferred (Remote / Hybrid flexibility)

Languages

  • SQL

Databases

  • SQL

Experience Level

  • Senior (6+ years) or Staff (9+ years)

We are partnering with a high-growth, global hospitality and commercial real estate platform to recruit exceptional engineering talent to build their next-generation technology foundation.


This is a high-impact, hands-on role for a full-stack engineer who thrives at the intersection of modern code, scalable architecture, and AI-first development.


The Opportunity

You will join a lean, high-caliber team responsible for building and modernizing everything from customer-facing digital experiences to the core operating engine running a global business.

  • Level: Senior (6+ years) or Staff (9+ years) — leveling will be tailored to your experience.
  • Compensation: $130,000 – $200,000 (commensurate with level and experience)
  • Location: East Coast US preferred (Remote / Hybrid flexibility).
  • Impact: High visibility; direct line to engineering leadership with zero bureaucratic friction.


What You’ll Do

  • Build End-to-End: Own features across the entire lifecycle—frontend, backend APIs, business logic, and relational data layers.
  • Cross-System Architecture: Connect enterprise systems (Salesforce, NetSuite) with custom internal applications and data pipelines.
  • Operate AI-Native: Integrate AI agents directly into your daily workflow across research, prototyping, implementation, and automated refactoring.
  • Set Technical Standards: Drive engineering best practices, design maintainable system patterns (KISS principle), and mentor junior/mid-level engineers.


What We’re Looking For

  • Experience: 6+ years of production software engineering (Senior) or 9+ years with cross-system architecture ownership (Staff).
  • Core Tech: Strong foundations in SQL, schema design, API architecture, web security, and cloud deployment.
  • AI Integration: Hands-on experience using AI agents for multi-step engineering tasks, setting agent context, and verifying output quality.
  • Product Mindset: You start with the problem before writing code, ask "why" before "how," and prioritize simple, resilient solutions.
  • Experience deploying LLM-backed features to production and building evaluation frameworks.
  • Familiarity with Model Context Protocol (MCP) servers, reusable skills, or repository automation instructions.
  • Background in event-driven systems, reverse ETL pipelines, or enterprise integrations (Salesforce/NetSuite).
  • Experience in hospitality, real estate, events, or multi-location businesses.