Global Red Team AI Engineer, Analyst

Requirements

• Familiarity with:
• REST APIs, OAuth/OIDC, JWT
• CI/CD pipelines or DevOps tooling
• Hands‑on experience using or experimenting with AI/LLM tools or prompt‑driven workflows.
• Familiarity with enterprise cloud AI platforms (e.g., Azure AI Foundry, AWS Bedrock, or GCP Vertex AI)
• Other:
• As per MUFG's work policy for all personnel, candidates must work onsite for 4 days and 1 day remotely.
• MUFG Benefits Summary
• We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with

Benefits

Additional Information

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. Job Summary: The Red Team Analyst supports MUFG Red Team operations by executing adversary‑emulation activities focused on AI‑enabled technologies. This role is designed for early‑career professionals with a computer science background and practical coding experience, enabling them to develop offensive security skills while contributing to risk reduction across the enterprise. Under the direction of senior operators, the analyst participates in threat‑led assessments, AI security testing, and purple team exercises, helping identify how real‑world adversaries could exploit application logic, automation pipelines, and AI‑assisted capabilities. Primary Responsibilities: Adversary Emulation & Testing Support Participate in Red Team missions designed to simulate real‑world attacker behavior against MUFG applications and platforms. Execute assigned activities during: adversary simulation and emulation (ASE) assumed‑breach scenarios purple team and control‑validation exercises Safely conduct testing activities aligned to approved scopes, deconfliction requirements, and operational guardrails. AI & Automation Workflow Testing Support adversarial testing of AI‑enabled capabilities, including: prompt injection and misuse scenarios unintended data access or disclosure via AI tools bypass of AI guardrails and safety controls Assist in assessing AI‑assisted developer tools, copilots, and automation platforms. Help evaluate how AI interacts with identity, permissions, APIs, and data sources. Tooling & Research Research emerging attacker techniques targeting: modern application stacks CI/CD and developer tooling AI/LLM systems Contribute to Red Team playbooks, test cases, and repeatable workflows. Support senior operators in engagement reporting and evidence collection. Participate in post‑engagement discussions with defensive and engineering teams. Develop and operationalize custom ML/LLM models for cybersecurity use cases Advance preventative, detective, and responsive security controls through applied AI innovation Evaluate emerging AI capabilities for cybersecurity and mature predictive, proactive threat response Required Qualifications: Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or equivalent practical experience. Demonstrated experience through internships, co‑ops, academic projects, or personal work. Strong analytical skills, attention to detail, and willingness to learn adversarial thinking. Hands-on experience with agentic AI, LLMs, and custom ML model development Proficiency with open-source AI frameworks and tooling (e.g., PyTorch, TensorFlow, SageMaker)

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