This role pays less than
73%
of similar roles. Most pay
$142,175–$202,925
— the shaded band above.
At the midpoint, this role pays about
$142k
versus about
$173k
for comparable roles.
Based on 240 similar postings.
Employer
About Booz Allen Hamilton
Booz Allen Hamilton is a management and technology consulting firm that provides analytics, digital, engineering, and cybersecurity solutions primarily to U.S. government agencies and commercial clients. Industry: Management & Technology Consulting
Booz Allen Hamilton currently has
799 open roles
on FindRole.
Listed pay typically runs
$86,800–$198,000
across 780 roles with salary data.
As a Scientific Software Engineer, you will join the development team to build custom tools, systems, and sites that ensure consistent performance and scalability for clients. You will manage code, develop regression testing protocols, maintain documentation, support release protocols, and triage bugs across various applications. The role focuses on modernizing complex modeling or computational systems, specifically supporting weather forecasting applications through backend development. You will work with Python, C, C++, Fortran, shell scripting, and HPC environments including MPI and OpenMP. Key responsibilities involve data assimilation workflows, model coupling, performance benchmarking, and automation of multi-step systems like UFS or HYCOM. The position requires expertise in Agile methodology, scientific DevOps, and CI/CD pipelines using GitHub Actions or GitLab. You will solve complex computational problems within cross-functional teams to optimize enterprise-scale scientific applications and numerical solvers.
Develop and maintain backend computational components including data assimilation workflows and model coupling systems.
Create custom tools, systems, and sites using modern architectural approaches and open-source frameworks.
Provide code management support for various applications and develop regression testing protocols.
Triage, investigate, and resolve bugs reported to supported applications.
Maintain up-to-date technical documentation and manage release protocols.
Optimize source code for scientific applications, numerical solvers, or coupled Earth-system models.
Automate multi-step systems and integrate workflows for large-scale modeling applications.
Perform performance benchmarking and ensure portability across high-performance computing (HPC) environments.
What we're looking for
5+ years of experience implementing and supporting Agile software development and scientific DevOps workflows for complex modeling systems.
5+ years of experience in software development using Python, C, C++, Fortran, shell scripting, or HPC programming environments like MPI and OpenMP.
Experience with scientific software engineering, product development, workflow automation, and code management in large-scale modeling applications.
Experience developing backend computational components including data assimilation, model coupling, performance benchmarking, and optimization for enterprise-scale systems.
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements.
Bachelor’s degree or 8+ years of software engineering experience in lieu of a degree.
Experience with containerization, CI/CD pipelines, and cross-platform HPC or cloud workflows (preferred).
Master's or Doctorate degree in Engineering, Computer Science, Computational Modeling, or a related field (preferred).
LabVIEW
C++
Python
National Instruments
cDAQ
cRIO
PXI
Data Acquisition
Distributed Systems
Network Communication
Unit Testing
Performance Optimization
Debugging