Develop and maintain Java and Spring Boot microservices for a distributed payments platform. Build payment methods, event-driven workflows, integrations, and production features with strong transactional consistency and idempotency. Write unit and integration tests, manage MySQL/Aurora persistence and migrations, and improve reliability through observability, resilience patterns, and safe deployments. Use GitLab CI/CD pipelines with Datadog deployment gates and collaborate on financial-grade systems.
We are looking for a Senior Java Engineer to build and maintain Java and Spring Boot services for a high-stakes, distributed payments platform.
The mandatory requirements are 4+ years of backend engineering with Java and Spring Boot, Apollo GraphQL client and Aurora MySQL with JPA/Hibernate experience, event-driven systems, and experience with financial-grade systems.
RECRUITMENT PROCESS
1. Application — Share a few details about your experience and background.
2. Coding Challenge — If applicable, complete it in the coding language you are most comfortable with.
3. Video Interview — Record a short video introduction in English.
4. Technical Interview or Hiring Manager Interview — Discuss your experience and fit for the role.
5. Offer — If it’s a match, you’ll receive an offer.
WHAT YOU’LL GAIN
• Remote work — Work from where you feel most productive.
• Local presence in India — Work in a structured and compliant environment aligned with Indian regulations.
• Competitive compensation in INR — Receive compensation in INR, plus support for learning, education, and wellness.
• Exciting projects — Work with modern technologies for global clients and fast-growing companies.
MUST HAVES
• 4+ years of backend engineering with Java and Spring Boot (Boot 3 preferred) in production microservices.
• Demonstrated ownership of production services in a distributed systems environment.
• Experience with GraphQL — either building APIs with Netflix DGS or consuming them via the Apollo Java/Kotlin client (Apollo GraphQL client experience required).
• Hands-on experience with AWS SQS, Apache Kafka, or RabbitMQ in event-driven, distributed systems.
• Strong JPA/Hibernate experience with MySQL/Aurora (Spring Data JPA), including transactional design and optimistic locking.
• Experience writing JUnit 5 unit tests with Mockito and integration tests against live environments.
• Proficiency with Gradle multi-module builds.
• Experience with GitLab CI/CD pipelines and Datadog (metrics and monitors).
• Comfortable using AI coding assistants (e.g., GitHub Copilot, Claude) responsibly to accelerate development while maintaining code quality and correctness.
• Experience with financial-grade backend systems where correctness, idempotency, and consistency are non-negotiable.
• Ability to reason clearly about transactional boundaries across external systems (e.g., a third-party billing platform plus a local metadata store).
• Have built or maintained a production Spring Boot service that consumes events from SQS, Kafka, or RabbitMQ.
• Have designed idempotent event handlers for workflows.
• Have written JPA entities and managed schema migrations against a production MySQL/Aurora database.
• Have integrated with an external REST- or SDK-based third-party platform.
• Have set up or worked with Datadog monitors as deploy quality gates in a CI/CD pipeline.
• Upper-intermediate English level.
NICE TO HAVES
• Prior experience in the Billing or Payments domain.
• Experience with DynamoDB (AWS SDK v2) and/or MongoDB (Spring Data) in a multi-store architecture.
• Experience with Netflix DGS.
WHAT YOU WILL DO
• Develop and maintain backend Java/Spring Boot services across the Payments platform.
• Add new payment methods to the platform's existing capabilities.
• Contribute to feature development, bug fixes, and reliability improvements across these services.
• Deliver production-ready feature work and bug fixes through GitLab CI, with unit and integration test coverage that meets Jacoco gates.
• Strengthen system reliability through improved observability, resilience patterns, and safe canary and production deploys gated by Datadog monitors.
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