Principal Research Scientist/Engineer Huntsville I/II/III/IV/V/VI/VII

Auburn University•Auburn, AL

4d•Onsite

About The Position

This position will be located in Huntsville, AL. The Charles D. McCrary Institute for Cyber and Critical Infrastructure Security at Auburn University seeks an experienced Principal Research Scientist/Engineer. This position will provide strategic and technical leadership for the design, development, deployment, and sustainment of advanced artificial intelligence, machine learning, software engineering, and solution architecture capabilities across the organization's research and technology portfolio. This position is responsible for overseeing AI/ML engineering, software delivery, enterprise solution architecture, DevSecOps practices, and secure technology deployment while ensuring scalable, reusable, and mission-focused solutions. The role leads the development of innovative AI-enabled capabilities supporting government, defense, and applied research initiatives, including AI-powered malware analysis, open-source intelligence (OSINT) platforms, maritime and rural health technology solutions, and other emerging technology applications. The position serves as a key technical leader in building internal engineering capacity, advancing software and AI modernization efforts, and transitioning critical architecture and development knowledge from external professional service providers to sustainable employee-owned capabilities. Through strategic planning, technical oversight, and team development, this role ensures the delivery of secure, high-quality solutions that support current and future mission requirements while strengthening the organization's long-term technical maturity and operational effectiveness.

Requirements

Must be a U.S. Citizen
Focus of Education: PhD from an accredited institution Engineering, Science, Management Information Science (MIS), or related technical field.
Scope of Expereince: Experience for Levels II-VII should be in engineering and research practices and principles or science-based programs.
Level I: No experience required
Level II: 2 years of professional experience
Level III: 4 years of professional experience
Level IV: 6 years of professional experience
Level V: 8 years of professional experience
Level VI: 10 years of professional experience
Level VII:12 years of professional experience
Substitutions for Experience: Candidates with a Bachelor’s or Master’s degree may substitute relevant experience toward the PhD requirement at the rate of two (2) years relevant experience per year of required education.

Responsibilities

Set and maintain the technical roadmap for AI, data, and software capabilities across Edge Lab programs.
Lead multidisciplinary research and development projects from problem framing and experimental design through prototype, validation, deployment, and transition.
Design and review software architectures, APIs, data pipelines, model-serving patterns, user-facing applications, and integration approaches.
Establish engineering practices for source control, automated testing, CI/CD, secure software development, documentation, code review, and release management.
Develop responsible AI and MLOps practices covering data governance, evaluation, model risk, monitoring, reproducibility, privacy, and lifecycle management.
Provide hands-on technical contributions in appropriate programming languages, cloud/on-premises platforms, AI frameworks, and data technologies.
Guide selection and integration of foundation models, machine-learning methods, retrieval systems, agents, and other AI techniques based on mission need and evidence.
Partner with the Technology Architect’s and Senior Cybersecurity Analyst's to ensure solutions are resilient, secure, observable, and deployable in customer environments.
Mentor engineers, researchers, students, and technical staff; assign work, review technical quality, and expand bench strength.
Develop technical concepts, proposals, budgets, schedules, demonstrations, reports, publications, and executive/customer briefings.
Lead knowledge transfer from software and AI consultants and assume ownership of reusable code, platforms, and technical decisions.