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Software Engineer, Python, DevOps

Job in Laurel, Howard County, Maryland, 20723, USA
Listing for: Johns Hopkins Applied Physics Laboratory (APL)
Full Time position
Listed on 2026-09-02
Job specializations:
  • Software Development
    Software Engineer, Python, DevOps, Cloud Engineer - Software
Salary/Wage Range or Industry Benchmark: 135000 - 180000 USD Yearly USD 135000.00 180000.00 YEAR
Job Description & How to Apply Below
Location: Laurel

Johns Hopkins Applied Physics Laboratory (APL) seeks a Software Engineer to build mission-critical systems for national security, space exploration, and health. You will design, implement, and test secure, scalable software in a collaborative, research-driven environment, working alongside scientists and engineers to solve real-world problems. Responsibilities include developing production-quality code, integrating with complex systems, and contributing to prototypes and tools. APL supports advanced training, graduate education, and professional growth while fostering an inclusive, ethical, and intellectually curious culture.

Responsibilities

  • Design, develop, test, and deploy software solutions for national security, space, and health missions.
  • Collaborate with scientists, engineers, and analysts to translate mission needs into robust software systems.
  • Implement secure, reliable, and scalable code following modern software engineering best practices.
  • Participate in code reviews, integration, and troubleshooting across complex systems.
  • Contribute to research prototypes and transition them into production-ready capabilities.
  • Document designs, interfaces, and test approaches to support maintainability and knowledge sharing.

Required Skills

  • Object-oriented programming (e.g., Java, C++, C#)
  • Python or similar high-level language
  • Software design and architecture
  • Secure coding practices
  • Linux/Unix development environments
  • Version control with Git
  • Unit, integration, and system testing
  • CI/CD pipelines and Dev
  • Ops tools
  • Cloud platforms (e.g., AWS, Azure, or similar)
  • Data structures and algorithms
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