Software Engineer - Internal Applications

Hermeus is a venture-backed defense aviation company reclaiming the lost art of rapid iterative prototyping to build the fastest aircraft in the world today. By prioritizing relentless hardware iteration, we deliver high-speed systems at the pace of the modern battlefield. We work with the Department of War to provide the high-speed capabilities our nation and its allies need to maintain a durable, asymmetric advantage.

Take technical ownership of internally developed applications as they transition from their original creators to IT. Learn and document existing application architecture, code, integrations, dependencies, data flows, and deployment processes. Maintain, troubleshoot, and enhance existing applications based on business requirements. Review AI-generated and rapidly developed code for reliability, security, maintainability, and technical debt. Refactor or redesign components where necessary to establish a sustainable production application. Develop new application functionality, APIs, integrations, and automation. Establish appropriate source control, branching, code review, testing, and release practices. Implement and maintain CI/CD pipelines and repeatable deployment processes. Partner with Infrastructure, DevOps, Security, and business stakeholders to ensure applications meet enterprise operational and security requirements. Implement appropriate authentication, authorization, logging, monitoring, secrets management, backup, and recovery capabilities. Troubleshoot production issues and perform root-cause analysis. Develop technical documentation and operational runbooks so applications can be supported by the broader IT organization. Evaluate AI-assisted development tools and techniques where they can improve development velocity without sacrificing maintainability or security. Help establish standards for transitioning future internally or AI-developed applications into production IT ownership.

5+ years of professional software development or application engineering experience. Strong experience maintaining and extending existing production applications, not only building new applications. Experience with modern application development frameworks and REST APIs. Experience working with Git-based source control and software development lifecycle practices. Experience troubleshooting applications across code, infrastructure, integrations, and data layers. Experience with cloud-hosted applications, preferably AWS. Experience with Docker and containerized application deployment. Working knowledge of CI/CD, containers, infrastructure concepts, and modern deployment practices. Understanding of application security fundamentals including authentication, authorization, encryption, secrets management, and secure coding practices. Ability to quickly understand unfamiliar codebases and architectures. Strong documentation and communication skills.

Experience with Python, JavaScript/TypeScript, or similar modern development languages. Experience with AWS services and cloud-native application architectures. Experience with Terraform or other Infrastructure-as-Code technologies. Experience integrating applications with enterprise platforms through APIs. Experience with identity platforms such as Microsoft Entra ID or Okta. Experience supporting applications developed using AI coding assistants, low-code platforms, or rapid application development approaches. Experience with relational databases, schema changes / migrations and data integrity. Familiarity with Kubernetes/EKS is a plus. Experience working in regulated or security-sensitive environments is a plus.

Within the first several months, this engineer will be able to independently understand and support the existing application(s), eliminate critical knowledge dependencies on its original developer, establish a reliable development and deployment process, address significant technical debt or security concerns, and begin delivering enhancements requested by the business. Longer term, this role will help establish a repeatable model for how internally developed and AI-assisted applications move from experimentation into secure, maintainable, production-supported services.

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