Lead Cybersecurity Architect, AI/Agentic Security

Job responsibilities

• Engages technical teams and business stakeholders to discuss and propose technical approaches to meet current and future cybersecurity needs
• Defines the technical target state of their cybersecurity product and drives achievement of the strategy
• Develop software, use firmwide AI/ML tools to enhance, automate, improve secure design and threat assessment processes.
• Own and drive SDRs for AI/ML platforms, agentic systems, and MCP integrations; document decisions, required controls, and risk acceptances
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support cybersecurity architecture workflows with strong validation habits and awareness of data sensitivity.
• Ability to assess and validate AI-assisted security recommendations before adoption, escalating uncertainty and ensuring outcomes align to security, resiliency, and auditability expectations.
• Define and govern secure reference architectures for agentic systems and MCP-enabled workflows, including isolation, segmentation, encryption, and identity management
• Define security requirements for authentication, authorization, data classification, and encrypted communications for MCP servers and agentic workflows
• Conduct and maintain threat models for agentic systems, MCP servers, and LLM Suite integrations, identifying and mitigating risks such as prompt injection, data leakage, and supply chain threats
• Required qualifications, capabilities, and skill
• Obtain 5+ years of cybersecurity architectural knowledge with hands-on practical experience delivering enterprise-level solutions and controls
• Advanced in one or more programming languages
• Hands on experience in coding and use AI / ML, agents to improve security assessments. Willing to work on POC on new innovative ideas
• Demonstrate ownership of Security Design Reviews (SDRs), security requirements, and architecture governance for large-scale platforms.
• Proven expertise in threat modeling and mitigating AI/ML risks such as prompt injection, data poisoning, model extraction/inversion, training data leakage, and third‐party/supply‐chain exposure.
• Strong hands-on technical depth across cloud and application security: IAM/least privilege, encryption & key management, secrets, network segmentation, secure APIs, logging/monitoring, and secure SDLC/CI/CD.
• Experience securing agentic AI systems and tool integrations (including MCP-based tool/data connectivity or similar protocols), with the ability to set guardrails for tool access, data handling, and runtime controls.
• Proficiency in all aspects of the Software Development Life Cycle
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., public cloud, artificial intelligence, machine learning, mobile, etc.)
• In-depth knowledge of the financial services industry along with their IT systems and experience communicating with senior leaders
• Ability to evaluate current and emerging technologies to recommend the best solutions for the future state architecture
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