Secure AI Engineer at Booz Allen in Washington, DC

Job description

• Are you looking for an opportunity to use your knowledge and technical skills to help organizations adopt artificial intelligence (AI) securely and responsibly. As a Secure AI Engineer, you'll combine your skills in AI engineering, cybersecurity, and offensive security to assess, harden, and improve AI-enabled systems. You'll have the chance to build your skills and solve real-world challenges in a fast-paced, agile environment. We are looking for someone like you to work closely with clients to design secure AI architectures, evaluate AI system resilience, identify vulnerabilities, and implement mitigations that enable safe deployment of generative AI and autonomous AI capabilities.
• As a Secure AI
• Engineer on our team, you'll advise clients on the secure design, deployment, and governance of AI systems and generative AI applications. You'll conduct AI red team assessments against large language models (LLMs), retrieval-augmented generation (RAG) systems, AI agents, and multi-agent workflows.
• You will identify and demonstrate AI-specific attack vectors, including prompt injection, jailbreaks, indirect prompt injection, data poisoning, model inversion, extraction, and other adversarial techniques. You will develop recommendations and technical mitigations to improve AI system security, resilience, and trustworthiness.
• You will build, test, and evaluate agentic AI systems using modern orchestration frameworks and assess their security posture, design security testing methodologies, automation, and tooling for AI applications throughout the development lifecycle, and adapt and extend open-source AI frameworks, security tools, and evaluation platforms to meet client-specific requirements.
• You'll stay current with emerging AI threats, vulnerabilities, research, and industry best practices in this fast-paced world of AI.
• Join us. The world can’t wait.

Responsibilities

• Advise clients on the secure design, deployment, and governance of AI systems and generative AI applications
• Conduct AI red team assessments against large language models (LLMs), retrieval-augmented generation (RAG) systems, AI agents, and multi-agent workflows
• Identify and demonstrate AI-specific attack vectors, including prompt injection, jailbreaks, indirect prompt injection, data poisoning, model inversion, extraction, and other adversarial techniques
• Develop recommendations and technical mitigations to improve AI system security, resilience, and trustworthiness
• Build, test, and evaluate agentic AI systems using modern orchestration frameworks and assess their security posture
• Design security testing methodologies, automation, and tooling for AI applications throughout the development lifecycle
• Adapt and extend open-source AI frameworks, security tools, and evaluation platforms to meet client-specific requirements
• Stay current with emerging AI threats, vulnerabilities, research, and industry best practices

Requirements

• 1+ years of experience developing applications using LLMs and modern AI frameworks
• 1+ years of experience building, deploying, or evaluating agentic AI systems
• Knowledge of AI security principles, secure AI development practices, AI attack techniques, and AI risk management
• Bachelor's degree
• Experience with AI red teaming frameworks such as Microsoft's PyRIT, Garak, Inspect AI, OWASP GenAI tools, or similar platforms, working with open-source software and modifying or extending existing frameworks to meet new use cases
• Experience performing security assessments, penetration testing, or offensive security activities
• Experience with agent orchestration frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, OpenAI Agents SDK, or similar technologies
• Experience implementing security controls for RAG systems, vector databases, AI gateways, and model-serving infrastructure
• Experience with containerization, Kubernetes, CI/CD pipelines, and Infrastructure-as-Code
• Experience contributing to or maintaining open-source projects
• Knowledge of AI security guidance and frameworks, including the OWASP Top 10 for LLM applications, NIST AI Risk Management Framework (RMF), MITRE ATLAS, and emerging AI security standards
• Knowledge of adversarial machine learning concepts
• Bachelor's degree in CS, Cybersecurity, or Engineering
• CISSP, OSCP, Security+, GIAC, or Cloud Security Certifications

Skills

Required

• Knowledge of AI security principles
• Knowledge of AI attack techniques
• Knowledge of AI risk management

Benefits

• At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.
• Salary at Booz Allen is determined by various factors, including but not limited to location, the individual’s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $77,600.00 to $176,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen’s total compensation package for employees. This posting will close within 90 days from the Posting Date.