Senior Security Engineer - AI

Position Overview MUFG seeks 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 and vulnerability prioritization. Advanced prompt engineering, designing high‑precision version‑controlled prompts and programmatically optimizing LLM outputs for reliable security logic and automated remediation scripts. Fine‑tune machine learning models (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, focusing on vector databases. Process Mapping & Optimization: Audit existing manual workflows, re‑engineer them with a “Machine‑First” mindset, and use 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 uphold ethical standards, data privacy, and “Human‑in‑the‑loop” checkpoints where necessary. Qualifications Expert‑level proficiency in Python with hands‑on experience in data ingestion, cleaning, and machine‑learning libraries (Scikit‑Learn, PyTorch). Experience in system and web‑based integrations. Proficiency with LangChain, CrewAI, or AutoGPT for agent orchestration. Hands‑on experience tuning machine‑learning models for a wide range of cyber‑security use cases. Hands‑on experience with at least one cloud AI solution (AWS Bedrock/SageMaker or Azure AI). DevOps skills: Docker, Kubernetes, and Git for version control and deployment. Deep experience with RESTful and GraphQL APIs to connect disparate systems. Bachelor’s or Master’s degree in Cybersecurity, Computer Science, Artificial Intelligence, or a related field; relevant industry certifications are also acceptable. Preferred certifications: GIAC Machine Learning Engineer, AWS Certified Machine Learning Engineer, Microsoft Certified: Azure AI Engineer Associate, CISSP. Compensation & Benefits Compensation: Base pay range: New York/New Jersey $140k–$203k; Other locations $140k–$185k. Potential discretionary performance‑based bonus and/or incentive compensation. Benefits: Competitive health & wellness benefits, retirement plans, educational assistance & training programs, income replacement for qualified employees with disabilities, paid maternity and parental bonding leave, paid vacation, sick days, and holidays. Work Arrangement Hybrid schedule: four days on site, one day remote. EEO Statement We are an equal‑opportunity employer. All qualified applicants, including those with criminal histories, will be considered for employment in accordance with applicable state and local laws and industry regulations. Visa Sponsorship Visa sponsorship is provided only on a business‑needs basis and is not guaranteed for this position. #J-18808-Ljbffr MUFG Bank, Ltd.