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# Software Engineer for AI-Native Platform & Integrations

- **Company:** Amazon.com, Inc.
- **Location:** Seattle, WA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $145,600.0 - $228,800.0
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Application Integration Architecture, Spreadsheets, Software as a Service, Software Debugging, Sync (Unix), OAuth, Software Engineering, Systems Integration, Backend, Rate Limiting, Front End Software Development, Pagination, Webhooks, GPT
- **Published:** August 4, 2026
- **Apply:** https://www.careerjet.com/job/register/us210d80166fad087aa145683a69b6fce0

## About the Role

* Strong, practical software engineering experience, able to ship end-to-end and unblock yourself.
 * Experience building SaaS products with APIs, data models, and production constraints.
 * Deep familiarity with integrations, including OAuth2, webhooks, API pagination, rate limiting, and sync semantics.
 * Comfort using AI coding tools such as Copilot or ChatGPT to accelerate development, while maintaining tests, well-designed interfaces, and guardrails.
 * Familiarity with MCP-style tool interfaces or experience building tool servers and runtime integrations.
 * Clear communicator, able to explain tradeoffs and keep stakeholders aligned.

## Description

Build an AI-native operations platform that replaces spreadsheet-driven processes with real-time dashboards and agentic workflows. This role owns end-to-end product delivery for platform foundations, integrations, analytics surfaces, and the pilot launch, shipping production features across backend and frontend. Key Responsibilities

 * Design, implement, and maintain the AI-native platform core, including entities, workflows, permissions, and multi-tenant foundations.
 * Build an omni-tool integration layer, including connectors to common tools, event ingestion, sync logic, and action execution.
 * Develop real-time analytics dashboards with live metrics, drill-downs, and export capabilities.
 * Architect an MCP-compatible agentic integration architecture, covering tool registry, permissions, runtime, and observability.
 * Ship production features across backend and frontend, and provide hands-on technical support during pilot launch, including debugging and iteration with real users.
 * Establish and maintain engineering hygiene, including testing, observability, and on-call readiness for pilot operations.
 * Iterate quickly and pragmatically, balancing speed with correctness and operational robustness.


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