Integrations Back-end Engineer

Required skills

Requirements

6+ years of back-end development experience
Experience with Node.js
Experience with AI-assisted engineering workflows (e.g. spec-driven development, agentic development, Cursor, Claude Code, Codex, Windsurf)
Experience reviewing and validating AI-generated code against strong engineering standards
Deep understanding of context engineering and task decomposition for coding agents
Experience with JavaScript/TypeScript
Experience with back-end frameworks (e.g. Express.js, NestJS)
Experience building and maintaining third-party API integrations
Experience with OAuth 2.0 / OpenID Connect, REST APIs, webhooks and token lifecycle management
Experience with event-driven systems and message queues (e.g. AWS SQS), including retries, dead-letter queues and backpressure
Experience with relational databases and ORMs (e.g. PostgreSQL, TypeORM)
Experience with cloud platforms and containers (e.g. AWS, Docker)
Ability to architect resilient distributed systems that depend on unreliable third-party APIs
Ability to explain where AI agents succeed, where they fail, and how their output is kept production-ready
Proficiency with testing, debugging, code review and PR development
Deep knowledge of OOP, SOLID and software design principles
Strong communication skills in both spoken and written English, with confidence in direct customer conversations

Strong communication skills in both spoken and written English, with confidence in direct customer conversations
Experience with AI-assisted engineering workflows

Startup experience
Experience with SAML 2.0, Microsoft Entra ID (Azure AD) or SCIM
Experience with Microsoft Graph and/or Google Workspace APIs
Experience integrating complex domain-specific platforms (e.g. construction software, ERPs, CRMs)
Experience developing internal AI engineering standards, tooling or workflows
Bachelor's Degree in Computer Engineering, Computer Science, or equivalent

Design, build, and maintain integrations with third-party platforms and APIs (e.g., construction ERPs, Microsoft and Google ecosystems, email and calendar providers, enterprise identity systems)
Implement OAuth 2.0 / OpenID Connect flows, secure token management, webhooks, and bidirectional data sync
Design queue-driven systems handling retries, rate limits, partial failures, backpressure, and eventual consistency
Build scalable backend services (e.g., Node.js, TypeScript)
Build comprehensive unit, integration, and end-to-end tests
Build and review production PRs, identifying architectural, security, performance, and maintainability issues in both human and AI-generated code
Apply modern AI engineering practices (e.g., specs, coding agents, AI editors, structured implementation, and review workflows) to increase development velocity
Own complex and ambiguous engineering problems from requirements through production
Work directly with customers, product managers, engineers, and external partners to translate requirements into technical solutions

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