Senior Backend Engineer - (Java/Spring Boot)

Gen Digital•New York, NY

1d•Hybrid

About The Position

MoneyLion, part of Gen, is seeking a deeply experienced backend engineer to help shape and scale the backend capabilities behind its product surfaces. The role calls for strong ownership, sound technical judgment, and a high bar for engineering quality. You will make architectural decisions, design resilient services, and build systems that support reliable customer and marketplace experiences. You will work closely with product, analytics, and engineering teams on partner integrations, experimentation, event quality, and core business workflows. The position involves designing scalable, modular, resilient backend systems; building dependable APIs, events, and service boundaries; and improving reliability, maintainability, observability, and operational excellence. You will also use AI tools to accelerate development while validating their output through sound engineering judgment, and maintain automated testing across multiple layers. The position is based in New York, NY, with onsite work three days per week. The expected annual base salary is $158,080–$178,880. Gen's total compensation package includes a 401(k) match, health insurance options, disability coverage, life insurance, and unlimited paid time off.

Requirements

Deep expertise in Java and Spring Boot, including building and operating production-grade services.
Strong understanding of REST API design, service contracts, and backward compatibility.
Experience designing and evolving distributed systems, including service decomposition and inter-service communication.
Solid understanding of data modeling and persistence, including SQL and NoSQL tradeoffs, indexing, and query performance.
Experience with asynchronous and event-driven architectures such as Kafka or SQS, including event design and reliability considerations.
Strong understanding of observability, including logging, metrics, tracing, and debugging production systems.
Experience implementing testing strategies across unit, integration, and contract testing layers.
Familiarity with CI/CD pipelines, Docker, and cloud-native environments such as AWS and Kubernetes.
Strong working knowledge of SQL and NoSQL databases.
Comfort designing and operating RESTful APIs, microservices, and distributed systems in production.
Familiarity with testing, monitoring, and modern development workflows, including Git-based workflows and containerized services.
Strong collaboration, communication, and problem-solving skills, including the ability to partner with Product, Analytics, and engineering teams in a fast-paced environment.
Bachelor’s degree in Engineering or a related field, or equivalent professional experience.
At least 5 years of software engineering experience, with a track record of building and shipping production applications.
Ability to thrive in a fast-paced, high-tech environment and manage complex problems.

Nice To Haves

Experience with high-scale, consumer-facing systems or marketplace platforms.
Familiarity with API gateways, rate limiting, and service-level protections.
Experience with data pipelines, event quality, and analytics instrumentation.
Hands-on experience with Claude Code or similar AI-powered IDEs and modern AI coding models.
Practical understanding of AI’s strengths and limitations, paired with sound engineering judgment.
Ability to use AI agents to explore implementation approaches, evaluate tradeoffs, and converge on robust solutions without creating fragile systems.

Responsibilities

Maintain a high bar for quality through design reviews, code reviews, testing, observability, and production readiness.
Partner with product, analytics, and engineering colleagues to shape solutions and deliver reliably.
Design and build scalable, modular, resilient backend systems that can adapt to evolving product and business needs.
Improve reliability, maintainability, observability, performance, and operational excellence across critical services and workflows.
Create dependable APIs, events, and service boundaries for partner integrations, experimentation, analytics, and downstream systems.
Use AI tools for prototyping, scaffolding, refactoring, and exploratory development, and validate their output with sound engineering judgment.
Build and maintain automated test coverage across unit, integration, contract, and end-to-end layers.