Offensive Security Engineer

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Lead Whitebox Penetration Testing: Execute end-to-end testing with full access to source code. You will perform manual code-level inspections to uncover complex logic flaws and authorization bypasses that automated tools miss.
Simulate Adversarial Attacks: Conduct Red and Purple team engagements across our cloud-native stack (K8s, Docker), simulating how a sophisticated actor might move from a code-level exploit to infrastructure-wide impact.
Secure AI-Enabled Systems: Perform offensive testing on LLM-backed applications and agentic AI workflows, focusing on prompt injection, data leakage, and abuse of AI-driven components.
Vulnerability Research & Chaining: Identify, exploit, and demonstrate realistic business risk by chaining vulnerabilities—from the application layer down through our internal trust boundaries.
Build Offensive Tooling: Contribute to internal security frameworks and build AI-assisted testing tools to automate the discovery of common bug classes while maintaining deep manual testing depth.
Partner with Engineering: Work closely with product teams and security architects to explain root causes, influence design guardrails, and triage high-priority findings from our Bug Bounty (HackerOne) program.

Experience: 7+ years of hands-on experience in penetration testing, offensive security, or vulnerability research.
Code Fluency: You are a practitioner of whitebox testing. You can navigate large codebases and have a deep understanding of modern application architectures and secure coding pitfalls.
Cloud-Native Context: You are comfortable in a cloud-native environment. While your focus is the code, you understand how it interacts with Kubernetes, Docker, and hybrid cloud infrastructure.
Engineering Skills: Strong proficiency in Go, Python, or TypeScript. You should be capable of writing custom scripts, payloads, and proof-of-concept exploits.
Adversarial Mindset: You enjoy the "hunt" and have a proven track record of manual exploitation beyond automated scanners.
Communicator: You can translate a complex code-level exploit into a clear narrative that helps engineering teams understand risk and prioritize fixes.

Public recognition on platforms like HackerOne or Bugcrowd.
Experience building or extending AI-based security testing tools.
Background in incident response or detection engineering from the defensive side.
Published CVEs or security research in the cloud-native or AI space.