Nango

Nango

Backend Engineer

USA

Sponsorship not specifiedDetected 48 days ago
Node.jsGitAWSProduct ManagementProduct StrategyCollaboration

About the role

  • (Remote - North America, LATAM or Europe) Nango https://nango.dev (YC W23) is a developer infrastructure company and the leading provider of API access for agents and apps.
  • It enables AI applications to connect to the real world through integrations.
  • If you're a seasoned backend engineer who loves developer infrastructure, thrives on ownership, and wants to shape the future of integrations - we'd love to hear from you.

Responsibilities

  • Design and scale backend systems, APIs, and services for our open-source platform.
  • Build world-class developer interfaces: APIs, SDKs, UIs, and a runtime that delights developers.
  • Optimize performance, scalability, and reliability across backend services.
  • Passion for developer tools, best practices, and building outstanding DX.
  • Product mindset and developer empathy: you optimize for DX.

Requirements

  • 5+ years (senior-level) or 10+ years (staff-level) of backend engineering experience, with proven ability to scale high-traffic systems.
  • Deep experience with developer infrastructure, APIs, databases, and performance-critical systems.

Company info

  • as a product-led business selling to developers, our engineers directly drive the product roadmap, specifications, and execution.
  • You will own core systems end-to-end, from ideation and design to implementation and close collaboration with developer customers, shaping both the platform and how Nango evolves.
  • Collaborate directly with customers to solve integration challenges.
  • Shape the roadmap and company strategy with high ownership of key decisions.
  • Engage with the open-source community, owning and maintaining our repo.
  • Comfortable with Node.js and modern backend stacks.
  • Strong communicator, proactive, and reliable in a remote-first environment.

This listing is sourced directly from Nango's careers page and normalized into a canonical job model.