Join one of the world's most influential companies and leverage your skills in cybersecurity to have a real impact on the financial industry.
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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