Captivation Software
Software Engineer 2 (Hybrid) - AWS/Hadoop/Accumulo/Terraform/Python/Java
About this role
Captivation Software seeks a mid-level software engineer with 14 years of experience to develop cloud-based solutions using AWS managed services, Hadoop, and related technologies. This hybrid role in Annapolis Junction, MD requires a Top Secret/SCI clearance and expertise across Java, Python, Terraform, and Accumulo.
What you'll do
- Develop and maintain software solutions on AWS using managed services
- Work with Hadoop and Accumulo for large-scale data processing
- Design and implement infrastructure as code using Terraform
- Collaborate with engineering teams on complex, mission-critical projects
- Contribute to code reviews and software process improvements
- Support government contracting programs with similar scope and complexity
What they're looking for
- AWS managed services
- Hadoop
- Accumulo
- Terraform
- Java
- Python
- Infrastructure as Code
- Large-scale data processing
Benefits
- Annual salary $130,000–$270,000 based on experience
- Up to 20% 401(k) contribution, vested immediately
- $3,600 HSA contribution
- 6 weeks paid time off
- Fully company-paid medical, dental, vision, life, and disability insurance
- Hybrid work arrangement
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Captivation Software
Captivation Software builds high-performance computing and secure analytics infrastructure for mission-critical government programs, specializing in HPC testing, enterprise dataflow architectures, and cleared defense systems. The company is hiring senior test engineers, systems engineers, and technical leaders with deep expertise in Linux, cloud infrastructure, and security clearances to validate systems and architect solutions for intelligence community operations.
View all jobs at Captivation SoftwareLikely interview questions
- Describe your experience architecting and deploying applications on AWS managed services—what specific services have you used most extensively?
- How have you used Hadoop and Accumulo in previous projects, and what challenges did you encounter with distributed data processing at scale?