Global Red Team AI Engineer, AVP

Assistant Vice President, Red Team & AI Security

Do you want your voice heard and your actions to count? Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), one of the world's leading financial groups. Across the globe, we're 150,000 colleagues, striving to make a difference for every client, organization, and community we serve. We stand for our values, building long-term relationships, serving society, and fostering shared and sustainable growth for a better world.

With a vision to be the world's most trusted financial group, it's part of our culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility. This means investing in talent, technologies, and tools that empower you to own your career.

Join MUFG, where being inspired is expected and making a meaningful impact is rewarded.

The selected colleague will work at an MUFG office or client sites four days per week and work remotely one day. A member of our recruitment team will provide more details.

The Assistant Vice President, Red Team & AI Security supports the planning, execution, and reporting of adversary simulation, control validation, and AI security assessment activities across the enterprise. This role is hands-on and operator-focused, combining offensive security tradecraft with AI analysis responsibilities to help identify exploitable weaknesses, validate defensive controls, and translate findings into practical remediation guidance.

• Support the planning and execution of Red Team, Purple Team, adversary simulation, and control validation engagements.
• Assist with target research, scope development, rules of engagement, infrastructure preparation, and operational documentation.
• Coordinate with defensive, engineering, risk, and business stakeholders to ensure engagements are well-structured and findings are actionable.

• Perform hands-on offensive security testing across network, endpoint, identity, application, cloud, and selected physical attack surfaces.
• Execute techniques such as reconnaissance, initial access validation, privilege escalation, lateral movement, persistence simulation, and control evasion in approved environments.
• Develop, modify, and safely use scripts, payloads, tooling, and tradecraft to support realistic adversary emulation.

• Support adversarial testing of AI and LLM systems, including prompt injection, data leakage, tool misuse, model behavior abuse, and guardrail bypass scenarios.
• Analyze AI-enabled applications, copilots, automation workflows, agents, plugins, APIs, and data integrations for security and abuse risks.
• Document AI security observations in clear business and technical terms, including risk impact, exploitability, control gaps, and recommended remediation.
• Use AI-assisted analysis responsibly to accelerate research, data review, reporting, detection mapping, and test-case development.
• Track emerging AI threats, attacker use of AI, and relevant industry guidance to inform Red Team scenarios and validation priorities.

• Drive research into real-world threat actor TTPs and emerging AI-enabled attack techniques.
• Sponsor development of red team tools, scripts, and repeatable methodologies to increase realism, scale, and efficiency.
• Establish standards for tooling governance, safe use, and audit readiness.

• Prepare engagement notes, evidence packages, attack narratives, findings, remediation guidance, and executive-ready summaries.
• Map observations to relevant frameworks, controls, detections, and business risk themes where appropriate.
• Partner with blue team, cyber defense, engineering, governance, and application teams to validate remediation and improve control effectiveness.

Experience

• 4+ years of experience in offensive security, red team operations, penetration testing, application security, cloud security, cyber defense, or related security assessment roles.
• Hands-on experience supporting security assessments, adversary emulation, control validation, vulnerability analysis, or threat-informed testing.
• Exposure to AI security, LLM testing, AI governance, data security, machine learning workflows, or secure…