Backend Engineer, Ops Engineering
at Ramp
New York, NY (HQ), remote, senior, full time, USD 1,68,000–2,84,900 / year, 5+ years
posted 04 Mar 2026
- TypeScript
- PostgreSQL
- Retool
- Redis
- Node.js
- Next.js
- Zendesk
- LLM
- React
- AWS
- Python
About the role
Remote: yes Posted: 2026-03-04
What you would do
- Design and build full-stack internal applications and tools that empower operations teams to work more efficiently and deliver exceptional customer experiences
- Develop robust backend services and APIs that power internal tooling, ensuring scalability, reliability, and performance
- Build integrations with third-party platforms like Retool, Zendesk, and other operational systems to create seamless workflows
- Leverage AI tooling and capabilities to build intelligent automation, enhance operator productivity, and improve decision-making within internal tools
- Create data-driven features and analytics that provide operations teams with actionable insights and improved visibility
- Collaborate closely with operations stakeholders to understand pain points, gather requirements, and iterate on solutions that solve real business problems
- Write clean, maintainable, and well-tested code following software engineering best practices
- Participate in code reviews, mentor team members, and contribute to the growth of engineering culture
- Own features end-to-end from design through deployment, monitoring, and iteration based on user feedback
- Participate in an On Call rotation to resolve critical issues impacting internal users
What they are looking for
- 5+ years of software engineering experience building and shipping production applications
- Strong proficiency in modern programming languages such as Python, TypeScript/Node.js, or similar
- Experience building full-stack applications with modern frameworks (React, Next.js, or similar for frontend)
- Solid understanding of backend architecture, API design, and database systems (PostgreSQL, Redis, etc.)
- Demonstrated aptitude for working with AI technologies, including experience integrating LLMs, building AI-powered features, or applying AI to solve business problems
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