Software Development Engineer - AI Focus

Onbe•Plano, TX

14h•Remote

About The Position

Onbe, a fast-growing FinTech, bringing innovation to a rapidly growing global marketplace, stands for “on behalf.” Because that’s exactly how we work: on behalf of our clients, as their comprehensive payments partner. We transform the way payments are imagined — as an opportunity for innovation, a source of insight to customers, and a way to connect with partners around the globe! Summary: We are looking for a Software Development Engineer with deep hands-on experience using AI coding agents as a primary development method. In this role, AI-assisted coding will be embedded throughout the daily engineering lifecycle: analyzing legacy systems, translating requirements into designs, generating and refactoring Java code, creating unit and integration tests, producing documentation, troubleshooting defects, and accelerating migration into independently deployable microservices. You will be expected to demonstrate proficiency with tools such as coding agents, prompt-driven development, and AI-generated test automation—not simply familiarity with them. Alongside strong Java and production engineering skills, you must be able to provide effective context to AI tools, review and improve their output, identify security and reliability risks, and take full ownership of the resulting production code. The target environment includes Java 21+, Spring Boot 3, Azure, REST APIs, event-driven integration, Docker, Kubernetes, and automated delivery.

Requirements

Bachelor’s degree in Computer Science, Information Technology, or a related field, or equivalent professional experience.
5+ years of professional software engineering experience, including substantial hands-on experience developing Java applications.
Strong experience with Java 21 or higher and modern Java development practices.
Strong hands-on experience using AI-assisted software engineering tools or coding agents, specifically Claude Code
Strong hands-on experience with Spring, Spring Boot, JPA/Hibernate, and REST API development.
Experience modernizing or migrating monolithic applications to microservices or cloud-native architectures.
Experience with relational databases, SQL, data modeling, transactions, and performance tuning.
Experience with automated testing frameworks such as JUnit, Mockito, and comparable integration or contract-testing tools.
Experience with Docker and Kubernetes; Azure Kubernetes Service experience is preferred.
Hands-on experience with cloud platforms, preferably Azure.
Experience with CI/CD, Git, Maven or Gradle, and deployment automation.
Ability to evaluate AI-generated code for correctness, security, maintainability, performance, and test coverage.
Strong communication, collaboration, problem-solving, and end-to-end ownership skills

Nice To Haves

Experience with Agile development methodologies
Experience in payments, fintech, banking, insurance, or another regulated industry.
Familiarity with payment processing, ledgers, settlement, ACH, cards, KYC, fraud controls, PCI, auditability, and sensitive-data protection.

Responsibilities

Design, develop, and operate production-grade Java microservices using Java 21 or higher and Spring Boot 3.
Partner with a core group of internal SMEs and an external vendor to decompose legacy Java and SQL monolith capabilities into independently deployable, domain-oriented services.
Serve as one of the long-term owners of the resulting domain service(s) once the vendor engagement concludes — driving its architecture, reliability, and evolution going forward.
Bring fresh, modern engineering perspective to legacy code and processes, challenging established patterns where a better approach exists
Develop and maintain secure RESTful APIs using Spring Boot and API-first design practices.
Implement event-driven integrations using Azure Service Bus or comparable messaging platforms.
Design and maintain data access layers using JPA/Hibernate, JDBC, and relational databases such as Azure SQL or Microsoft SQL Server.
Build automated unit, integration, API contract, regression, and end-to-end tests, following TDD and shift-left quality practices.
Use AI coding agents and other AI-assisted engineering tools to generate, refactor, test, document, and troubleshoot software while reviewing and owning the final output.
Containerize and deploy services using Docker, Kubernetes, Azure Kubernetes Service, or Azure Container Apps.
Contribute to CI/CD pipelines, infrastructure automation, service configuration, secrets management, observability, and production support.
Monitor application performance, availability, and reliability; participate in incident response and continuous improvement.
Collaborate with product, architecture, platform, security, QA, and business-domain teams to deliver complete solutions.