K

KX

Time-aware data platform powering AI insights

Java Engineer

Backend EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Strong experience with Java 17 and the Spring Framework, including MVC and Security.
  • Experience with Apache Tomcat deployment and tuning.
  • Proficiency with Maven/Nexus and GitLab CI/CD.
  • Understanding of distributed systems, clustering, and failover.
  • Strong knowledge of web security standards and the OWASP Top 10.
  • Familiarity with the Linux environment.
  • Eight or more years of professional Java development experience.
  • Enterprise-level backend or middleware experience.
  • Experience with Spring, distributed systems, and authentication/authorisation frameworks.
  • Experience collaborating with DevSecOps and Support teams.

Responsibilities

  • Develop, maintain, and optimise Spring-based web applications and REST APIs using Java 17.
  • Integrate backend services with real-time kdb+ environments.
  • Implement authentication using SAML/LDAP and secure authorisation using RBAC/ABAC.
  • Participate in distributed system design, including failover, replication, and node synchronisation.
  • Apply secure coding practices to mitigate XSS, CSRF, SQL injection, and related vulnerabilities.
  • Deploy and tune applications on Apache Tomcat.
  • Develop unit, integration, and system-level tests.
  • Collaborate with DevSecOps on CI/CD pipelines and automated testing.
  • Support production investigations with the Support team.

Desired Qualifications

  • Exposure to front-end technologies, Python scripting, or AI/ML APIs.
  • Experience with real-time or time-series databases.
  • Knowledge of kdb+ or similar high-performance data engines.
  • Experience with legacy modernisation projects.

About the Company

KX

Time-aware data platform powering AI insights

KX provides a data and analytics foundation that delivers time-aware, complete, and timely data to power AI-enabled decision making. It collects and harmonizes large datasets, tracks how data changes over time, and runs scalable analytics and dashboards optimized for AI workloads. This helps fast-moving organizations generate faster and more accurate insights at any scale with cost efficiency. Its focus on change-over-time data and scalable performance helps sectors like finance, aerospace, manufacturing, healthcare, automotive, and fleet telematics maximize AI value and outpace competitors.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
Newry, United Kingdom
Founded
1993

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