Senior AI Security Software Engineer

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%)

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