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LogicGate is seeking a Platform Software Engineer to build robust backend services, APIs, and data layers powering Risk Cloud, the company's AI-driven GRC (Governance, Risk, and Compliance) platform for enterprises.
In this role, you will work autonomously within an assigned domain to design stable solutions, ship high-impact features, and systematically debug production workloads. You'll take ownership of backend feature engineering—designing and building REST APIs using Java, Kotlin, and Spring Boot from requirements through production release. You'll write clean, testable code with comprehensive unit and integration tests using JUnit, contributing to a stable deployment lifecycle.
You'll act as a subject matter expert for a defined portion of the platform (such as the workflow engine or reporting services), independently diagnosing and resolving issues within your service area using distributed logs, monitoring systems like Datadog, and customer session analytics. You'll work operationally with relational databases (PostgreSQL), advanced data stores (Neo4j, Redis), and messaging infrastructure (RabbitMQ) to optimize data flow across microservices.
You'll participate in Technical Specification reviews, estimate effort accurately, and author clear technical documentation including API contracts and runbooks. Cross-functional collaboration is key—you'll partner with product managers, QA engineers, and frontend developers in Agile sprints, raising dependencies and blockers daily. You'll actively participate in peer code reviews, providing meaningful feedback and receiving constructive input with curiosity to learn.
Required: 3–5 years of professional backend, platform, or systems engineering in high-growth environments. Strong proficiency in Java, Kotlin, or comparable JVM languages with Spring Boot experience. Solid experience building and maintaining production-grade REST APIs with versioning and contract stability. Practical experience with relational databases (PostgreSQL), including complex queries, schema migrations, and query performance analysis. Demonstrated ability to independently debug distributed services using logs, monitoring tools, and security platforms. Practical experience using AI coding assistants (Cursor, GitHub Copilot, Claude Code) as part of your normal workflow.
