[Hiring] AI Security Engineer @Microsoft

Role Description

The Cloud & AI organization accelerates Microsoft's mission to secure digital technology platforms, devices, clouds, and AI systems across customers' heterogeneous environments and Microsoft's internal estate. Our culture is centered on a growth mindset, inspiring excellence, and helping teams and leaders bring their best every day.

Microsoft Red Team (MRT) emulates real-world advanced persistent threats against Microsoft, external customers, and frontier AI systems. As AI systems become increasingly capable at reasoning, coding, tool use, exploitation, and autonomous execution, understanding when and how those systems materially increase offensive cyber capability is an important component of Microsoft's AI security mission.

MRT Strategic AI is seeking an AI Security Engineer focused on Cyber Capability Evaluation. This is a hands-on technical role for implementing and executing evaluations of frontier AI models and agentic systems in realistic, controlled cyber environments. The engineer will work at the intersection of offensive security, AI agents, model evaluation, and experimental engineering to build and maintain evaluation tasks, run experiments, analyze model behavior, and determine whether observed results represent meaningful cyber capability, an evaluation artifact, or a limitation in the test environment.

The role requires the ability to work independently within established technical direction, solve engineering and security problems, and contribute improvements to evaluation methods, cyber ranges, scoring, telemetry, and containment. The right candidate combines offensive-security experience with experimental discipline, programming skills, and an interest in emerging AI capabilities.

Responsibilities

• Design, implement, and operate offensive cyber-capability evaluations for frontier, preview, production, and open-weight AI models.
• Build and maintain realistic evaluation tasks covering vulnerability analysis, exploit development, application and system exploitation, attack-path reasoning, post-exploitation activities, and multi-step offensive workflows.
• Execute controlled experiments using AI models; define success criteria and baselines; collect reliable telemetry; and document results.
• Analyze model trajectories and investigate unexpected behavior to determine whether it reflects genuine capability, task leakage, environmental flaws, scoring errors, or other evaluation artifacts.
• Develop and maintain cyber ranges, vulnerable applications, exploit-development targets, and evaluation harnesses, and apply security controls for sandboxing, secrets management, telemetry, access, and containment when testing autonomous AI systems.
• Partner with red-team operators, researchers, engineers, and Responsible AI stakeholders to translate evaluation findings into security insights, and communicate results through reports, documentation, and briefings.

Qualifications

• Master's Degree in Statistics, Mathematics, Computer Science, Computer Security, or related field AND 1+ year(s) experience in software development lifecycle, large-scale computing, threat analysis or modeling, cybersecurity, vulnerability research, and/or anomaly detection.
• OR Bachelor's Degree in Statistics, Mathematics, Computer Science, Computer Security, or related field AND 2+ years experience in software development lifecycle, large-scale computing, threat analysis or modeling, cybersecurity, vulnerability research, and/or anomaly detection.
• OR equivalent experience.

Requirements

• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
• Microsoft Cloud Background Check: This position will be required to pass the Microsoft background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.
• This role will require access to information that is controlled for export under export control regulations.
• This position requires verification of citizenship due to citizenship-based legal restrictions.

Preferred Qualifications

• Doctorate in Statistics, Mathematics, Computer Science, Computer Security, or related field OR Master's Degree in Statistics, Mathematics, Computer Science, Computer Security, or related field AND 3+ years experience in software development lifecycle, large-scale computing, threat analysis or modeling, cybersecurity, vulnerability research, and/or anomaly detection.
• OR Bachelor's Degree in Statistics, Mathematics, Computer Science, Computer Security, or related field AND 5+ years experience in software development lifecycle, large-scale computing, threat analysis or modeling, cybersecurity, vulnerability research, and/or anomaly detection.
• Programming ability, particularly in Python, with experience building automation, scripts, or security tooling.
• Familiarity with large language models, generative AI systems, coding models, AI agents, or model APIs.
• Ability to follow experimental methodology, record results accurately, and document technical findings clearly.
• Exposure to security labs, cyber ranges, capture-the-flag environments, or vulnerable applications.
• Experience contributing to cyber-capability evaluations or model-evaluation work for AI or agentic systems.
• Coursework, internship, competition, or project experience in exploit development, vulnerability research, penetration testing, application security, or red teaming.
• Experience working with coding agents, tool-using models, or autonomous agent frameworks.
• Experience building capture-the-flag challenges, vulnerable applications, or exploit-development targets.
• Familiarity with PyRIT, adversarial-testing tools, or comparable model-evaluation frameworks.
• Familiarity with containers, sandboxed execution, or cloud-based test infrastructure.
• Hands-on cybersecurity experience with systems, networks, applications, vulnerability analysis, penetration testing, red teaming, or exploitation in authorized environments.
• Experience working with large language models, generative AI systems, coding models, AI agents, model APIs, or model-evaluation frameworks.
• Experience designing controlled experiments, defining success criteria, analyzing results, and documenting technical findings.
• Familiarity with common evaluation risks, including contamination, task saturation, unreliable scoring, weak baselines, environmental leakage, and limited reproducibility.

Benefits

• Security Research IC3 - The typical base pay range for this role across the U.S. is USD $102,100 - $202,200 per year.
• Security Research IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year.
• There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area.
• Certain roles may be eligible for benefits and other compensation.