Job description

The CERT Division of the Software Engineering Institute (SEI) is seeking applicants for the role of Senior AI Security Software Engineer. Established in response to the Morris worm, CERT has been a leader in cybersecurity research, advancing the resilience of software systems and responding to sophisticated cyber threats. As AI becomes central to critical infrastructure, advancing its security and resilience offers a compelling opportunity to shape the future, impacting support of the national security mission. Our team researches and develops tactics, techniques, and procedures necessary for the field of AI security. Our work includes experimental designs for large-scale AI security research programs, AI red teaming, and counter AI applications. Additionally, we work in generative AI and large language models, data visualization, security analysis of AI systems, and adversarial machine learning. We have access to a wide variety of cyber-related data, including malware samples, NetFlow data, cyber security training runs and tests, incident tickets, and more. Artificial Intelligence Security Software Engineers at the SEI use software and machine learning engineering practices, data processing, and data analytics to help our researchers solve AI security challenges. In this role, you will work with our researchers and customers to develop machine learning based prototypes, products, and tools to solve and automate solutions to AI Security problems. You ll get a chance to work with elite AI and cyber security professionals and university faculty to build new technologies that will influence national AI and cyber security strategy for decades to come. Key Responsibilities Develop machine learning–based prototypes, tools, and systems for AI security applications, demonstrating strong expertise in ML development and deployment Collaborate with researchers and stakeholders to design and execute experimental AI security solutions, communicating effectively across technical and non-technical audiences Apply software engineering best practices to build scalable, maintainable systems, grounded design principles Process and analyze large, diverse cybersecurity datasets (e.g., malware, NetFlow, incident data), using strong analytical and problem-solving skills Support AI red teaming and adversarial machine learning initiatives, applying an innovative and research-driven mindset Translate research concepts into practical, operational capabilities, with the ability to work independently and as part of a collaborative team Minimum Qualifications BS in computer science, machine learning, cybersecurity, statistics, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years of experience; OR PhD in the same fields with five (5) years of experience Understanding of software engineering principles and system design Experience with containerization and microservices architectures Travel to various locations to support the SEI’s overall mission. This includes within the SEI and CMU community, sponsor sites, conferences, and offsite meetings on occasion (5%).  You will be subject to a background check and will need to obtain and maintain a Department of War (DoW) security clearance. Preferred Qualifications Experience applying statistical modeling and advanced data analytics techniques Background in developing AI/ML solutions in real-world settings Familiarity with applied machine learning domains (e.g., natural language processing, computer vision, autonomy, audio analysis) Experience and knowledge in cybersecurity best practices Demonstrated ability to quickly learn and adapt to new technologies and domains Why Join Us Contribute to a world-class organization with significant impact on software and national security Work with cutting-edge technologies alongside leading experts in AI, cybersecurity, and software engineering 8% employer retirement contribution (no employee contribution required) Tuition benefits for employees and their dependent children Flexible work arrangements and strong work-life balance Paid parental and military leave Professional development opportunities, including conference attendance and certifications Qualify for relocation assistance and so much more. Location Arlington, VA, Pittsburgh, PA Job Function Software/Applications Development/Engineering Position Type Staff – Regular Full time/Part time Full time Pay Basis Salary More Information: Please visit “ Why Carnegie Mellon ” to learn more about becoming part of an institution inspiring innovations that change the world. Click here to view a listing of employee benefits Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran . Statement of Assurance

Requirements

Must-haves

Develop machine learning–based prototypes, tools, and systems for AI security applications, demonstrating strong expertise in ML development and deployment
Collaborate with researchers and stakeholders to design and execute experimental AI security solutions, communicating effectively across technical and non-technical audiences
Apply software engineering best practices to build scalable, maintainable systems, grounded design principles
Process and analyze large, diverse cybersecurity datasets (e.g., malware, NetFlow, incident data), using strong analytical and problem-solving skills
Support AI red teaming and adversarial machine learning initiatives, applying an innovative and research-driven mindset
Translate research concepts into practical, operational capabilities, with the ability to work independently and as part of a collaborative team
Understanding of software engineering principles and system design
Experience with containerization and microservices architectures
Travel to various locations to support the SEI’s overall mission. This includes within the SEI and CMU community, sponsor sites, conferences, and offsite meetings on occasion (5%).
You will be subject to a background check and will need to obtain and maintain a Department of War (DoW) security clearance.

Nice-to-haves

Experience applying statistical modeling and advanced data analytics techniques
Background in developing AI/ML solutions in real-world settings
Familiarity with applied machine learning domains (e.g., natural language processing, computer vision, autonomy, audio analysis)
Experience and knowledge in cybersecurity best practices
Demonstrated ability to quickly learn and adapt to new technologies and domains

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningml

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Vision

Professional Development