Redhorse Corporation is transforming how the Department of Defense (DoD) utilizes data and technology, seeking to advance data-driven decision-making across the DoD by designing and implementing robust data solutions that directly impact national security initiatives and investments.
Requirements
- Programming expertise in Python, JavaScript, and at least one additional modern programming language.
- Experience with frontend frameworks such as React, Vue, or similar.
- Backend development experience with frameworks/runtimes such as Node.js, Spring/Spring Boot, Django, Flask, or equivalent.
- Experience with Agile software development methodologies and associated tools.
- Strong understanding of modern software architectures, including microservices and component-based frontend frameworks.
- DevSecOps experience is highly preferred.
Responsibilities
- Design and develop software architectures, APIs, frameworks, and libraries supporting intelligence-focused and mission-aligned capabilities.
- Build both frontend and backend components for prototypes, reusable tooling, and production-ready systems.
- Guide the development and maintenance of common code libraries and shared tools used across multiple teams and products.
- Support strategy development for rapid prototyping of AI and Generative AI capabilities.
- Create prototype components and reference implementations to accelerate experimentation and capability deployment.
- Document software requirements, specifications, and system interfaces; review technical documentation produced by vendors and partner teams.
- Develop reference architectures, compliance standards, and technical roadmaps to ensure alignment across system components and stakeholders.
Other
- Secret clearance required. Top Secret with SCI eligibility highly desired.
- Excellent communication skills and the ability to translate requirements into actionable engineering solutions.
- Ability to synthesize and prioritize feature requests, recommend alternative technical approaches, and support engineering execution on aggressive timelines.
