This role pays less than
57%
of similar roles. Most pay
$142,400–$203,525
— the shaded band above.
At the midpoint, this role pays about
$162k
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
802 open roles
on FindRole.
Listed pay typically runs
$86,800–$198,000
across 783 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, maintain CI/CD pipelines, develop regression test protocols, and coordinate with component model repositories to ensure seamless system integration across all supported platforms. Your daily work involves designing data handling workflows, optimizing model performance, conducting benchmarking, and supporting distributed computation. The role requires expertise in Fortran, C++, Python, MPI, OpenMP, and containerized workflows like Docker or Singularity. You will also utilize cloud HPC platforms such as AWS, GCP, or Azure while integrating APIs and managing complex modeling system workflows. This position focuses on modernizing large-scale scientific and computational systems, specifically addressing the technical challenges of weather and climate modeling platforms used in research and operational forecasting environments.
Develop and maintain backend components for large-scale scientific and computational systems.
Create custom tools, systems, and sites using modern architectural approaches and open-source frameworks.
Manage code repositories and maintain CI/CD pipelines to ensure seamless system integration.
Develop and maintain regression test protocols and conduct frequent version releases.
Design data handling workflows and optimize model performance for distributed computation on HPC and cloud platforms.
Debug technical issues and ensure the adoption of software development best practices.
Test modeling infrastructure across all supported platforms to ensure consistent performance and scalability.
What we're looking for
Experience implementing and supporting Agile software development for large-scale scientific or computational systems.
Experience developing and integrating software using Fortran, C++, Python, MPI, OpenMP, or containerized workflows.
Experience with scientific DevOps, product management, and complex modeling system workflows.
Experience developing backend components, designing data handling workflows, and optimizing performance for distributed computation on HPC and cloud platforms.
Ability to solve complex technical problems within collaborative, cross-functional scientific or engineering teams.
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements.
Bachelor’s degree or 12+ years of experience in software engineering in lieu of a degree.
LabVIEW
C++
Python
National Instruments
cDAQ
cRIO
PXI
Data Acquisition
Distributed Systems
Network Communication
Unit Testing
Performance Optimization
Debugging