Lead Web Proxy & AI Security Engineer - Vice President

Morgan Stanley • Dallas, TX

13d

About The Position

We are seeking an engineer to accelerate enterprise AI adoption by building, integrating, and optimizing secure access to approved AI tools and model endpoints through web security gateways, proxy infrastructure, and AI security controls. This role sits at the intersection of AI platform engineering, network/security architecture, and developer enablement. The engineer will design and operate the technical controls that allow employees and applications to use sanctioned LLMs safely, reliably, and with acceptable performance. This includes secure routing, policy enforcement, DLP integration, model access governance, observability, and latency optimization across secure web gateways, CASB, API gateways, reverse proxies, and related control planes.

In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Principal Cyber Security Engineering position at the Vice President level, which is part of the job family responsible for providing specialist cyber expertise and creating solutions that protect the organization's systems and networks against actual and potential security threats and vulnerabilities.

Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Cybersecurity, or related field, or equivalent practical experience.
• 5+ years of experience in engineering and design of web security and ZTNA platfoms in Netskope, Zscaler, Palo Alto, Fortigate.
• Fluency in AI application protocols such as WebSocket, Server Sent Events, gRPC, and experience in troublshooting AI connverastions from OpenAI, Anthropic, Grok, MSFT Copilot, Cowork, for both GenerativeAI and AgenticAI
• Hands-on experience with secure web gateways, proxies, CASB, SSE/SASE, WAF, API gateways, or related access-control technologies.
• Experience integrating enterprise applications with REST APIs and cloud services.
• Strong understanding of authentication and authorization patterns, including SSO, OAuth, OIDC, mTLS, and service-to-service identity.
• Experience with DLP, data security controls, logging pipelines, and policy enforcement in enterprise environments.
• Strong scripting or programming skills in Python, Go, Java, or similar.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Ability to troubleshoot across network, security, application, and platform layers.
• Strong written and verbal communication skills with the ability to explain technical tradeoffs to security, risk, and business stakeholders.

Nice To Haves

• Experience securing or enabling access to LLMs, GenAI platforms, or model APIs.
• Experience with AI gateways, model routing, prompt filtering, token-aware controls, or AI observability tools.
• Knowledge of enterprise controls around data residency, privacy, records retention, and regulated data handling.
• Experience with tools such as Netskope, Zscaler, Palo Alto, Cloudflare, Akamai, Azure API Management, Kong, Apigee, or similar platforms.
• Familiarity with Kubernetes, service mesh, reverse proxies, and zero-trust access patterns.
• Experience supporting regulated environments such as financial services, healthcare, or public sector.
• Exposure to model risk, AI governance, or third-party technology risk frameworks.

Responsibilities

• Design and implement secure access patterns for enterprise AI services behind secure web gateways, AI gateways, proxies, and cloud security controls.
• Enable access to sanctioned LLMs and AI applications while blocking or restricting unsanctioned services.
• Partner with security, infrastructure, legal, risk, and application teams to onboard AI use cases in a controlled manner.
• Build traffic-routing, authentication, and policy-enforcement mechanisms for user-to-AI and app-to-AI interactions.
• Integrate DLP, data classification, logging, redaction, token filtering, and content inspection into AI traffic flows.
• Optimize latency, throughput, reliability, and user experience for AI access paths traversing security gateways.
• Develop guardrails for prompt/response inspection, data exfiltration prevention, tenant isolation, and approved use enforcement.
• Implement monitoring and alerting for model usage, blocked events, policy violations, response times, error rates, and adoption metrics.
• Support evaluation and rollout of technologies such as secure web gateways, CASB, SSE/SASE, AI gateways, API management, and service mesh controls.
• Create reusable patterns, reference architectures, and onboarding playbooks for AI application teams.
• Perform root-cause analysis for performance bottlenecks, access failures, and policy conflicts affecting AI use cases.
• Contribute to standards for AI access, third-party model connectivity, secrets management, and auditability.
• Document architecture decisions, operational procedures, and control evidence for internal governance and regulatory review.

Benefits

• Ample opportunity to move about the business for those who show passion and grit in their work.
• Attractive and comprehensive employee benefits and perks in the industry.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal