US- Java Engineer - Pricing
Confirmed on the employer's own hiring board on Oct 13, 2026. First seen by Alion on Oct 12, 2026.
About the Role & Team Culture:
We are looking for strong Engineering and Product professionals who excel in a dynamic environment. At MoneyGram, we value engineers who can navigate ambiguity without waiting for direction and take ownership of outcomes rather than simply completing tasks. In this role, you will be expected to make sound decisions using available information, communicate proactively, and balance autonomy with collaboration. We are building a culture where individuals seek solutions rather than assigning blame, always aiming to build trusted relationships across functions while maintaining a steadfast focus on business and customer outcomes over functional wins.
Job Summary:
We are seeking a highly skilled a Java Engineer with 2-5 years of experience to contribute to the design, development, and deployment of our high-volume enterprise applications. In this role, you will architect and build robust, secure, and compliant transactional backend systems, optimize billing/pricing engines, and drive technical excellence. You will collaborate closely with cross-functional teams to build high-performance, low-latency financial software hosted on AWS.
Core Responsibilities:
Architect, design, and implement high-availability, fault-tolerant enterprise Java applications.
Write clean, secure, and highly optimized code utilizing modern Java features to handle large-scale financial transactions.
Design and scale distributed microservices architectures optimized for transactional consistency and speed.
Optimize complex data models, design transactional database schemas, and manage relational and NoSQL databases.
Build and secure robust APIs for seamless third-party financial network integrations and ERP connections.
Manage and automate secure cloud-based deployment pipelines using modern DevOps practices on AWS.
Lead code reviews, enforce strict financial security coding standards, and mentor engineering team members.
Identify financial transactional bottlenecks, optimize query performance, and ensure zero-downtime production deployments.
Required Technical Skills:
Core Tech: Java 17 / Java 21, Spring Boot, Spring Cloud, Hibernate ORM, and JPA.
Architecture: Microservices, Event-Driven Architecture, CQRS, Distributed Transactions (Saga pattern), and Domain-Driven Design (DDD).
Databases: PostgreSQL, Oracle DB and Couchbase.
Messaging & Streaming: Apache Kafka.
Cloud & DevOps: AWS (highly preferred; experience with Azure or GCP is acceptable), Docker, Kubernetes, and Jenkins or GitLab CI.
Testing & Tools: JUnit 5, Mockito, Testcontainers, automated contract testing, Maven, or Gradle.
Experience Requirements:
Minimum 2 to 5 years of professional backend software engineering experience.
Proven track record of working on large-scale distributed systems, enterprise SaaS products, or transactional banking/financial applications.
Extensive experience building and deploying software within Agile/Scrum environments.
Demonstrated experience migrating monolithic applications to distributed microservices architectures.
Qualifications & Competencies:
Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field (or equivalent practical experience).
Strong system-level troubleshooting skills with the ability to make sound decisions using available data.
Self-starter mindset with the ability to navigate ambiguity and execute tasks without waiting for step-by-step direction.
Exceptional proactive communication skills to build trusted relationships and influence outcomes across cross-functional teams.
Excellent English written and verbal communication skills
Preferred (Good to Have) Skills:
Direct experience building or maintaining complex pricing-related applications, financial billing engines, monetization platforms.
Hands-on technical exposure or integration experience with OUAF Framework or Oracle Revenue Management System (ORMB).
Familiarity with integrating Machine Learning models into Java backends, using AI APIs, or implementing predictive intelligence for financial workflows (e.g., fraud detection, intelligent routing).
Hands-on experience with Google Cloud Platform analytics tools such as BigQuery, Looker, Cloud Dataflow, or Dataproc for financial data processing.