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. Role Overview: MUFG is seeking a highly motivated Security Engineer to design, develop, and deploy autonomous agents that eliminate manual overhead and drive intelligent decision-making across the organization while ensuring proper guardrails and security controls are implemented. Key Responsibilities • Agentic Workflow Design: Build and maintain AI agents capable of multi-step reasoning and tool-use to automate cyber security use cases such as Autonomous Incident Investigation, vulnerability prioritization. • Advanced Prompt Engineering with expertise in designing high-precision, version-controlled prompts with ability to programmatically optimize LLM outputs for reliable security logic and automated remediation scripts. • Use and fine-tune machine learning models (like Deep Learning, K-MEANS, SVM etc) to identify sophisticated attack patterns that bypass traditional signature-based defenses. • LLM Integration: Integrate large language models (OpenAI, Anthropic, or open-source models into production environments via APIs or local deployments. • Data Pipeline Orchestration: Develop and optimize data ingestion pipelines, specifically focusing on Vector Databases • Process Mapping & Optimization: Audit existing manual workflows and re-engineer them using a "Machine-First" mindset, utilizing LLMs to handle unstructured data. • Infrastructure & MLOps: Deploy and monitor AI solutions using cloud-native tools, ensuring high availability, low latency, and cost-efficiency. • Safety & Compliance: Implement guardrails for AI outputs to ensure ethical standards, data privacy, and "Human-in-the-loop" checkpoints where necessary. Qualifications: • Expert-level in Python with hands-on in data ingestion, cleaning, machine learning libraries covering Scikit-Learn, Pytorch, system and web-based integrations. • AI Frameworks: Proficiency with LangChain, CrewAI, or AutoGPT for agent orchestration. • Machine Learning: Hands-on experience in using and tuning Machine Learning models for wide range of cyber security use cases. • Hands-on experience with atleast on the cloud AI solution (AWS Bedrock/SageMaker, Azure AI) • DevOps: Docker, Kubernetes, and Git for version control and deployment. • Deep experience with RESTful and GraphQL APIs to connect disparate systems. Education: • Bachelor's or Masters degree in Cybersecurity, Computer Science, Artificial Intelligence or related field, or relevant industry certifications. Equivalent work experience is equally preferable. Preferred Certifications: • GIAC Machine Learning Engineer • AWS Certified Machine Learning Engineer • Microsoft Certified: Azure AI Engineer Associate • Certified Information Systems Security Professional (CISSP) "Visa sponsorship/support is based on business needs. We do not anticipate providing visa sponsorship/support for this position." The typical base pay range for this role is as follows: • New York / New Jersey: $140k - 203K depending on job-related knowledge, skills, experience and location. This role may also be eligible for certain discretionary performance-based bonus and/or incentive compensation. Additionally, our Total Rewards program provides colleagues with a competitive benefits package (in accordance with the eligibility requirements and respective terms of each) that includes comprehensive health and wellness benefits, retirement plans, educational assistance and training programs, income replacement for qualified employees with disabilities, paid maternity and parental bonding leave, and paid vacation, sick days, and holidays. For more information on our Total Rewards package, please click the link below. Our hybrid work schedule is four days on-site and work remotely one day per week. MUFG Benefits Summary