Staff Application Security Engineer

Brex Brex · Fintech · Remote · Engineering

Staff Application Security Engineer focused on securing Brex's AI-driven financial services, including agentic features and LLM architectures. Responsibilities include defining security vision, leading vulnerability management, and mentoring teams, with a strong emphasis on AI security practices like prompt injection and data poisoning mitigation.

What you'd actually do

  1. Lead the technical vision and strategic roadmap for the Application Security team, aligning security objectives with Brex's enterprise growth and high-velocity engineering metrics.
  2. Establish technical standards and secure defaults across the entire engineering organization, fostering a culture of collaborative security excellence and bridging product platforms, infra, and trust.
  3. Architect and secure novel AI/ML and agentic workflows, applying cutting-edge practices to mitigate risks such as prompt injection, model manipulation, and data poisoning.
  4. Mentor and coach engineers within the team and across the broader organization, guiding technical growth, helping individuals level up their security expertise, and accelerating team delivery.
  5. Drive proactive vulnerability discovery and offensive security testing strategies, executing complex attack chains to demonstrate business impact and prioritize cross-functional remediation.

Skills

Required

  • Application Security
  • Product Security
  • software engineering
  • penetration testing
  • vulnerability management
  • AI security
  • agentic architectures
  • LLM gateways
  • adversarial AI vectors
  • threat modeling
  • cloud-native container security
  • AWS
  • Kubernetes
  • Python
  • Go

Nice to have

  • Kotlin
  • gRPC
  • GraphQL
  • Kubernetes
  • building and scaling security teams
  • securing distributed systems in AWS
  • open source contributions
  • public research
  • CTF participation
  • blogging
  • CVEs
  • presentations
  • bug bounty programs
  • responsible disclosure programs
  • AI security research
  • AI security frameworks

What the JD emphasized

  • Deep proficiency and technical expertise in AI security, including hands-on experience securing agentic architectures, LLM gateways, and evaluating adversarial AI vectors.
  • Architect and secure novel AI/ML and agentic workflows, applying cutting-edge practices to mitigate risks such as prompt injection, model manipulation, and data poisoning.

Other signals

  • securing novel AI implementations
  • identifying emerging attack vectors in agentic-powered features
  • hardening distributed LLM architectures
  • securing agentic architectures, LLM gateways
  • evaluating adversarial AI vectors