Sr Cyber Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Cyber Engineer based in the United States. The Senior Cyber Engineer will design, implement, and operate advanced security controls to protect enterprise AI applications, infrastructure, networks, and sensitive member data. This hands-on role focuses on securing emerging generative AI technologies, including large language models, AI agents, and Model Context Protocol (MCP) servers, while strengthening core security platforms. You will take technical ownership of Cloudflare and Palo Alto Networks environments, developing protections against prompt injection, data leakage, unauthorized access, and automated abuse. Working closely with Application Security, Architecture, Data, Privacy, and Compliance teams, you will translate security requirements into practical, enforceable controls. You will also contribute to detection engineering, incident response, automation, and continuous security improvement. This is a remote opportunity for an experienced security engineer who enjoys solving complex challenges and building production-ready defenses in an evolving technology environment. Accountabilities In this role, you will lead the engineering and operation of AI security controls while maintaining enterprise-grade network and edge protection. You will be accountable for deploying reliable solutions, improving security visibility, and ensuring that controls perform effectively in production. Your responsibilities will include: - AI Application Discovery and Governance: Build visibility into enterprise AI applications, coding assistants, agents, and MCP servers, including unsanctioned tools. Establish risk-based policies to allow, monitor, isolate, or block their use.

- AI Data Protection: Design and optimize data loss prevention (DLP) controls for prompts, file uploads, model responses, and agent tool calls, protecting protected health information (PHI), personally identifiable information (PII), and financial data. - AI Runtime Security: Deploy protections for production AI applications and agents, including prompt injection and jailbreak detection, sensitive data identification, topic and output controls, token-based rate limiting, and secure audit logging. - AI Agent Access Management: Define authentication requirements and access permissions for AI agents interacting with internal systems. Ensure tool calls are logged and attributable to the relevant person or service, govern approved MCP connections, and block unauthorized access paths. - AI Gateway Management: Centralize traffic to large language model providers through managed AI gateways, enforcing security policies and providing usage, cost, and credential visibility. Ensure API keys are securely stored in secrets vaults rather than source code, configuration files, or pipelines. - Bot and Agent Protection: Collaborate with Product and Fraud Prevention teams to define how member-facing and employer-facing websites and APIs handle AI crawlers and agents, implementing appropriate controls through Cloudflare Bot Management. - Adversarial Testing: Conduct security testing against AI applications and agents, focusing on prompt injection, data exfiltration, tool misuse, and privilege abuse. Translate findings into stronger controls and detection capabilities. - Secure Architecture Collaboration: Partner with Application Security, Architecture, Data, Privacy, and Compliance teams to assess proposed AI use cases, develop secure reference architectures, and implement enforceable security requirements. - Cloudflare Platform Engineering: Own and operate Cloudflare services, including WAF, API Shield, Bot Management, DDoS protection, rate limiting, DNS, TLS, and Cloudflare One capabilities such as Access, Gateway, Tunnel, CASB, DLP, and Browser Isolation.