Provide technical leadership for a team of software engineers Develop software utilizing C/C++ to modernize and productionize a research codebase Identify and define software infrastructure to support CI/CD, software metrics collection, and MLOps Design and implement software-systems, applications, and architectures that leverage techniques to support achieving increased modularity, scalability, and reliability, while also maintaining precision, accuracy, and speed to meet performance requirements Ensure industry software engineering best practices and standards are applied and maintained Present your ideas to internal and external groups; lead proposal activities; and represent Northrop Grumman at technical conferences and working groups Work closely with Software Architects to define and understand program intent, system capabilities, and output requirements Bachelor's degree in a STEM discipline with 12+ years of relative experience; Master's degree in a STEM discipline with 10+ years of relative experience; PhD + 8 years of relative experience Active Top Secret security clearance Ability to meet customer-specific security screening requirements within a timeframe set forth by management Willingness and ability to work onsite full-time Experience working in C/C++ Demonstrated experience with open software/system architecture solutions Demonstrated ability to analyze system requirements to derive software design and performance requirements Proven ability to design and code new software, as well as modify existing software to add new features Ability to debug existing software and correct defects 1 or more years of experience leading the performance of tasks on schedule, at cost and achieving all requirements 1 or more years of demonstrated success leading teams through the entire development lifecycle Proven experience presenting complex topics to management and other stakeholders. Effective communication and interpersonal skills, with the ability to collaborate effectively with diverse stakeholders Experience with Git-based or other software configuration management tools Ability to define technical strategy to modernize/productionize research code Experience with model-based system engineering tools (Cameo) Experience with containers (Docker, Kubernetes) Experience with Linux operating systems Experience with CUDA and GPUs Experience with high performance numerical/scientific computing, parallel computing Experience with developing for SWaP-constrained environments Experience with MLOps and integrating ML models into production code Familiarity with signal-processing algorithms Familiarity with Agile lifecycle process including Scrum, CI/CD, and DevSecOps