Full Stack AI Engineer, Global Information Security (Vice President)

Overview

Global Information Security is building and operating software that helps security teams work more effectively. We are looking for a hands-on full-stack engineer to turn operational needs into reliable, secure products used by analysts and engineers across multiple regions.

The core of this role is software development: designing and delivering useful user interfaces, back-end services, APIs and data flows, then supporting those systems in production. You will collaborate with teams across Security Operations, identity and access management, privileged access management, cloud security, network security, data protection and vulnerability management.

Automation and AI may be part of a solution, but they are not the starting point for every problem. We value strong engineering fundamentals, sound technical judgment and the ability to build and maintain software, not simply generate code or assemble prototypes. You should be comfortable using development tools, including AI coding assistants, while remaining able to understand, test, debug and take responsibility for the code you deliver.

Responsibilities

• Design, build and maintain full-stack applications, including user-facing interfaces, back-end services, APIs and data integrations.
• Maintain and extend agentic AI workflows, including agent nodes, prompts, guardrails, tool bindings and human-in-the-loop approval gates, alongside evaluation and bias governance activities.
• Manage data models and pipelines in MongoDB/DocumentDB, ensuring data quality, synchronization integrity across systems of record and auditability.
• Own AWS infrastructure via Infrastructure as Code (IaC) and CI/CD; manage environments, releases, security posture (SSO/RBAC) and cost optimization.
• Maintain observability through dashboards, agent audit trails, structured logging, alerts and operational runbooks.
• Partner with security teams to understand operational challenges, shape requirements and deliver practical software solutions that analysts can adopt in their daily work.
• Write readable, maintainable code and contribute to scalable application architecture, automated testing, code reviews and technical documentation.
• Build and maintain REST APIs and integrations with platforms such as SIEM, EDR, SOAR, PAM, IGA, CSPM, DLP, ticketing and threat intelligence systems.
• Create and maintain CI/CD pipelines that automate build, test, security checks and deployment.
• Package and run services using Docker and contribute to deployments in Kubernetes-based environments.
• Operate production software through monitoring, alerting, incident investigation, reliability improvements and lifecycle management.
• Apply secure development practices, including input validation, secrets management, least-privilege access, audit logging and appropriate approval controls.
• Identify where workflow automation or AI can improve a process and where a deterministic software solution is more appropriate.
• Develop AI-enabled features and workflow integrations, including LLM APIs, tool calling and MCP integrations, with appropriate evaluation and human oversight where suitable.
• Measure the impact of delivered software through adoption, time savings, reduced cycle times, accuracy improvements and service quality metrics.
• Collaborate with colleagues and stakeholders across time zones, sharing knowledge and contributing to engineering standards and documentation.
• Mentor engineers and support consistent delivery practices across the global team.

Required Qualifications

• At least 5 years of professional software engineering experience, including responsibility for production systems.
• Demonstrated full-stack development experience delivering both user-facing applications and back-end services.
• Strong proficiency in at least one modern front-end framework and language, such as React with TypeScript/JavaScript, and one back-end language such as Python, Java, C# or Node.js.
• Experience designing and integrating REST APIs, handling authentication and working with relational or document-oriented databases.
• Strong engineering fundamentals, including automated testing, debugging, code review, version control and maintainable software design.
• Practical experience creating or maintaining CI/CD pipelines for automated build, test and deployment.
• Working knowledge of Docker, including building and troubleshooting container images and running containerized applications.
• Familiarity with Kubernetes concepts, including pods, deployments, services, configuration and logging.
• Understanding of Terraform and Infrastructure as Code principles.
• Experience applying secure development practices, including secrets management, access control, input validation and auditability.
• Ability to take a loosely defined problem from discovery through implementation, release and production support.
• Experience working with distributed teams and stakeholders across multiple time zones.

Preferred Qualifications

• Experience in financial services or another regulated industry, including familiarity with audit, evidence and change-control requirements.
• Experience building software and agentic workflows for security operations or other security domains such as IAM, PAM, cloud security, network security, data protection or vulnerability management.
• Experience integrating enterprise platforms using webhooks, event-driven architectures or workflow automation tools.
• Practical experience using LLM APIs, agent runtimes or MCP integrations in software products.
• Familiarity with AI-related risks such as prompt injection, unsafe tool use and excessive autonomy, along with mitigation strategies.
• Experience with production observability, including structured logging, metrics, tracing and alerting.
• Experience using AI coding assistants responsibly, with the ability to review, test and explain generated code.
• Experience transitioning vendor-managed software or automation to internally owned services.
• Open source contributions, published research or conference speaking experience.

Candidate Profile

The successful candidate is a software engineer first: someone who can understand a problem, select an appropriate design and deliver a complete, supportable solution. They are comfortable moving between front-end and back-end development, building integrations, improving pipelines and diagnosing production issues.

They take ownership of their work and can explain the code they write, including code developed with assistance from automation or AI tools. They value testing, review and maintainability and understand that a working demonstration is only the beginning of a production-ready service.