Who you are
This role is ideal for an engineer who executes with efficiency and takes operational ownership within their scope of responsibility, while actively developing the depth to shape our future enterprise cloud architecture
Professional Experience: 3–5 years of professional backend, platform, or systems engineering experience within a high-growth environment
Core Stack Proficiency: Strong development experience using Java, Kotlin, or a comparable enterprise JVM language, alongside practical exposure to frameworks like Spring Boot
API Design Mastery: Solid experience building, owning, and maintaining production-grade REST APIs, with an emphasis on API versioning, contract stability, and cross-team consumer workflows
Database Fundamentals: Practical experience working with relational databases (such as PostgreSQL), including writing complex queries, executing schema migrations, and analyzing query performance
Autonomous Troubleshooting: Demonstrated ability to independently debug complex distributed backend services by parsing logs, utilizing monitoring systems like Datadog, and verifying compliance protocols via security tools like GitLab Ultimate, Sonarqube and Wiz.
AI-Augmented Development: Practical experience using AI coding assistants (Cursor, GitHub Copilot, Codex, or Claude Code) as part of a normal workflow—writing effective prompts, building reusable skills or custom instructions, and knowing when to trust, verify, or discard AI-generated output
Polyglot Exposure: Experience or fluency with Go (our platform chapter utilizes Go alongside our primary JVM stack)
Advanced Data Infrastructure: Familiarity with graph databases (Neo4j), message queues (RabbitMQ), or distributed caching layers (Redis)
SaaS Architecture: Background building multi-tenant B2B SaaS applications where strict data isolation, high availability, and performance at scale are paramount
Modern Distributed Systems: Deep understanding of event-driven architectures, microservices patterns, or containerized applications at production scale
What the job involves
As a Platform Software Engineer at LogicGate, you will build the robust backend services, APIs, and data layers that power Risk Cloud. Working autonomously within an assigned domain, you will design stable solutions, ship high-impact features, and systematically debug production workloads
Feature Engineering: Design and build backend features and robust REST APIs on the Risk Cloud platform using Java, Kotlin, and Spring Boot—taking engineering tasks from requirements through implementation, testing, and production release
Quality Assurance & Testing: Write clean, understandable code and build comprehensive unit and integration tests using JUnit, adhering to the testing pyramid to contribute to a highly stable, dependable deployment lifecycle
Systematic Debugging: Independently diagnose and resolve issues within your owned service area by reading distributed logs, analyzing console data, tracing request flows, and utilizing customer session analytics without needing escalation for routine anomalies
Domain Ownership: Act as a subject matter expert (SME) for a defined portion of the platform (such as our core workflow engine or reporting services), gathering context independently to design functions optimized for maintainability and scalability
Architecture & Documentation: Participate productively in Technical Specification reviews, estimate level of effort accurately, and author clear technical documentation including API contracts, data models, and Confluence runbooks
Data Management: Work operationally with relational databases (PostgreSQL) and advanced platform data stores (Neo4j, Redis) alongside messaging infrastructure (RabbitMQ) to trace, query, and optimize how data flows across microservices
Agile Collaboration: Partner cross-functionally with product managers, QA engineers, and frontend developers in Agile sprints, mapping out individual task prioritization while raising dependencies or project blockers daily to ensure engineering alignment
Code Reviews & Culture: Participate actively in regular peer code reviews—providing meaningful praise, ensuring compliance with team conventions, and receiving constructive feedback non-defensively with an innate curiosity to learn
Benefits
47 days off starting your first year, including paid volunteer time
12 weeks parental leave
$1,000 annual educational stipend
Ongoing learning and development
Stock options and annual performance bonus opportunities