Lead Infrastructure Security Engineer

About AngelList

AngelList is building the financial infrastructure that private markets never had—equivalent to exchanges, custodians, and brokers in public markets. Today, AngelList supports $200B+ in assets and 30,000+ startups funded across its platform.

About the Role

As a Lead Infrastructure Security Engineer, you will design and build systems that make security a fundamental property of AngelList's infrastructure: a unified identity and access layer, cloud security, automated provisioning and revocation, and developer guardrails that maintain development velocity.

You will partner directly with Infrastructure, Engineering, IT, and Product teams. This role reports to the Head of Security on a small team with broad scope.

Responsibilities

• Own AngelList’s security foundations across AWS infrastructure, identity, access control, authentication, authorization, and secrets management.
• Design and build security architecture and guardrails into infrastructure-as-code, CI/CD, and developer workflows to establish automatic secure defaults.
• Build IAM systems and least-privilege access models scaling across employees, services, and machine identities, including access reviews and privileged access.
• Write security tooling and automation to identify and remediate weaknesses autonomously, harnessing AI to improve decision quality.
• Address security risks at the platform and architectural level, contributing to application security through threat modeling, secure design, and vulnerability remediation.

Qualifications

• 7+ years of experience across security engineering, cloud security, infrastructure security, or identity, including hands-on AWS/GCP security architecture and IAM.
• Ability to write production software, automation, and internal tooling to solve security challenges.
• Proven track record driving security improvements across engineering teams via influence and developer tooling.
• Proficiency in infrastructure-as-code, CI/CD, and modern DevOps practices.
• Systems-level thinking to eliminate whole classes of problems rather than individual findings.
• Experience building with AI to improve workflows and operational efficiency.

Workplace & Location

• Hybrid in-office model: at least 2 days per week in-office (Tuesdays and either Wednesday or Thursday).
• Primary engineering hub located in San Francisco, CA (NYC may also be considered).