Back-End Software Engineer

LogicGate; United States; On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

47 days off starting your first year,

12 weeks parental leave

$1,000 annual educational stipend

Ongoing learning and development

Stock options and annual performance-

bonus opportunities

Job summary

LogicGate is seeking a Platform Software Engineer to build robust backend services, APIs, and data layers that power Risk Cloud. You will own a domain, design stable solutions, and ship high-impact features while debugging production workloads with minimal escalation.

You will design and build REST APIs with Java, Kotlin, and Spring Boot, write unit and integration tests, and contribute to a scalable multi-tenant SaaS platform using Postgres, Neo4j, Redis, and RabbitMQ.

Qualifications

• 3–5 years of backend, platform, or systems engineering experience in a high-growth SaaS environment.

Responsibilities

• Build robust backend services, APIs, and data layers powering the Risk Cloud platform.
• Design and ship high-impact features with Java, Kotlin, and Spring Boot.
• Write clean code and comprehensive unit and integration tests (JUnit).
• Diagnose and resolve issues by reading logs, tracing requests, and using monitoring tools.
• Own a defined portion of the platform, driving maintainability and scalability.
• Contribute to API contracts, data models, and Confluence runbooks.
• Work with PostgreSQL, Neo4j, Redis, and RabbitMQ to optimize data flows.
• Collaborate with product, QA, and frontend teams in Agile sprints.
• Participate in peer code reviews and promote a culture of learning.

Skills

Java / Kotlin

Spring Boot

APIs / REST

Distributed systems

Go

Tools

PostgreSQL

Neo4j

RabbitMQ

Redis

Datadog

GitLab

SonarQube

Wiz

Job description

• 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

This role is ideal for an engineer who executes with efficiency and takes operational ownership within your scope of responsibility, while actively developing the depth to shape our future enterprise cloud architecture

• 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
• Database Fundamentals: Practical experience working with relational databases (such as PostgreSQL), including writing complex queries, executing schema migrations, and analyzing query performance
• 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
• Core Stack Proficiency: Strong development experience using Java, Kotlin, or a comparable enterprise JVM language, alongside practical exposure to frameworks like Spring Boot
• Professional Experience: 3–5 years of professional backend, platform, or systems engineering experience within a high-growth environment
• 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