Software Back End Engineer

GDIT is a global technology and professional services company delivering technology solutions and mission services to government, defense, and intelligence organizations. The Mid-Level Backend Engineer will design, build, test, deploy, and support backend services and APIs that process and validate high-volume application data, while collaborating across teams and contributing to code quality and operational health.

Responsibilities:

• Design, build, and maintain backend services and APIs that process and validate application data
• Implement business rules ("edits") and calculations correctly, with meaningful test coverage, where our standard is 90%+ line and branch coverage
• Write clean, readable, maintainable code that the next engineer can extend without fear
• Collaborate with product, QA, and other engineers to turn ambiguous requirements into well-scoped, shippable work
• Participate in code reviews – giving and receiving thoughtful, specific feedback
• Contribute to operational health: logging, metrics, configuration management, and diagnosing production issues
• Make and document design trade-offs (rule representation, error handling, extensibility, performance) and defend them in review

Requirements:

• Back-End Development, Code Reviews, Design
• 3 + years of related experience
• Yes
• 3–7 years of professional backend software engineering experience
• Solid experience in any major programming language – Java, JavaScript/TypeScript, Python, Go, C#, or similar – or across a spectrum of them. We care about breadth of exposure and depth of understanding, not a specific language on your résumé
• Ability to read and review logic critically. AI is a leveler on syntax and boilerplate; what sets engineers apart now is judgment – spotting flawed logic, reasoning about correctness, and reviewing code (yours and others') with a critical eye
• Solid grasp of designing and consuming HTTP/REST APIs
• Demonstrated commitment to testing – you write tests as part of building, not after
• Comfort with relational databases and data modeling
• Experience with version control (Git) and collaborative workflows (branching, PRs/MRs, code review)
• Ability to make pragmatic design decisions and clearly explain the why
• Clear written and verbal communication
• 10-25%
• Familiarity with TDD is a plus
• Experience in regulated, high-accuracy, or high-volume data domains (financial, government, healthcare)
• Familiarity with rules engines, validation frameworks, or configuration-driven business logic
• Exposure to distributed systems concepts (async processing, throughput/latency trade-offs, CAP)
• CI/CD, containerization, and cloud deployment experience
• Comfort using modern AI development tools (Claude, Copilot, ChatGPT) as part of a professional workflow