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# Software Development Engineer

- **Company:** Earnin
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $152,000.0 - $185,800.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automation of Tests, Code Coverage, Software Quality, Computer Engineering, Continuous Integration, Cursor (Graphical User Interface Elements), Programming Tools, Service Design, Software Engineering, Systems Architecture, GitHub Copilot, Large Language Models, Backend, Build Management, Kubernetes, Information Technology, Restful APIs, GPT, Microservices, Data Generation
- **Published:** August 6, 2026
- **Apply:** https://www.dice.com/job-detail/5f30c68c-8c70-49cd-b222-75d90f3f2caf

## About the Role

* 7+ years of software engineering experience building production backend services, with a strong track record of writing high-quality, well-tested, maintainable code
 * Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related technical discipline, or equivalent industry experience
 * Demonstrated experience designing and building testability infrastructure, internal developer tools, or platform services consumed by other engineering teams
 * Strong hands-on experience building and maintaining RESTful APIs and services in a microservices architecture (REST and gRPC)
 * Proven ability to design safe, access-controlled "test-only" interfaces or hooks into production-adjacent systems without introducing security or reliability risk
 * Solid understanding of software quality methodologies and how to translate them into platform capabilities rather than manual processes
 * Experience with CI/CD tooling and integrating testability/quality tooling into build and deployment pipelines
 * Excellent written and verbal communication skills, with experience influencing and evangelizing engineering practices across teams without direct authority
 * Experience with Kubernetes and microservice architecture is a strong plus
 * Genuine enthusiasm for AI-native/AI-first engineering - hands-on experience using LLMs/AI agents to generate tests, synthetic data, or automate quality workflows, and a point of view on where AI should (and shouldn't) be trusted in a testability platform
 * Experience using AI-assisted development tools (e.g., GitHub Copilot, Cursor, ChatGPT, or similar tools) as part of your software development workflow?

## Description

We are looking for an experienced, passionate, and resourceful Software Development Engineer (SDE) to join our team and own testability as a first-class engineering discipline. This is not a QA role - you are a builder. You will design, build, and maintain the services, tools, and RESTful APIs that make our fintech systems inherently testable, observable, and safe to change quickly. You'll partner closely with engineering teams across the org to embed testability and quality practices directly into how services are architected and shipped - not bolt them on after the fact. You'll have the chance to work on interesting fintech problems and make a real difference in the lives of our customers by making our engineering org faster and safer to ship in., * Design, build, and maintain backend services and RESTful APIs that expose testability as a platform capability (e.g., test hooks, state seeding/reset, fault injection, synthetic data generation, environment control)

 * Architect and implement "backdoor" testing interfaces and controlled test-only entry points that allow engineering and automation teams to safely manipulate system state, simulate edge cases, and validate behavior without compromising production integrity or security
 * Evangelize testability and quality engineering practices across cross-functional teams (product, backend, mobile, data science, design) - influencing how services are designed from day one to be observable, controllable, and verifiable
 * Partner with development teams to understand product and system architecture, identifying testability gaps in microservices (REST and gRPC) and proposing platform-level solutions
 * Build and own internal tooling, SDKs, and libraries that make it easy for any engineering team to adopt testability best practices with minimal friction
 * Define and track quality and testability metrics/SLAs across services; drive adoption through data, not mandate
 * Collaborate with and mentor engineers across teams, providing technical guidance on test architecture, service design, and quality engineering patterns
 * Work closely with security and platform teams to ensure testability features (backdoors, hooks, overrides) are safely scoped, access-controlled, and cannot be exploited in production
 * Champion AI-native/AI-first approaches to testability and quality - using AI/LLM-based tooling to auto-generate test cases, synthetic data, and edge-case scenarios, and to accelerate root-cause analysis of failures
 * Build and integrate AI-powered agents into the testability platform (e.g., agents that can autonomously exercise APIs, detect regressions, or generate test coverage reports) to scale quality engineering beyond manual effort
 * Evaluate and pilot emerging AI coding/testing tools, establishing patterns for how engineering teams org-wide should adopt AI-assisted development and testing responsibly


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