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Staff + Software Security Engineer, Secure Frameworks

Menlo Ventures Portfolio

New York, NY · full time · Senior

$32,000 – $485,000

Listed on Menlo Ventures Portfolio’s own careers site. You apply with them directly — we never stand between you and the employer.

What this role is

Build and operate foundational security systems serving Anthropic's engineering organization, including cryptographic frameworks, identity services, and zero-trust access infrastructure. This role suits experienced security engineers who enjoy shipping production systems and can drive adoption across teams with minimal oversight.

Our summary, not Menlo Ventures Portfolio’s wording. The full posting is on their site.

Skills this role names

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What they ask for

Required

  • 8+ years building security-relevant systems in production with independent leadership of complex initiatives
  • Strong programming in Go, Rust, or Python
  • Deep knowledge of authentication and authorization systems including OAuth 2.0, OIDC, JWTs, and policy-based access control
  • Hands-on experience with PKI, X.509, mTLS, and workload identity
  • Working knowledge of applied cryptography including primitive selection, key management, and practical library failure modes
  • Production experience operating high-reliability services on Kubernetes across cloud and on-premises with on-call responsibilities
  • Track record of clarifying and owning ambiguous technical problems across teams
  • Strong developer experience mindset
  • Clear communication across organizational levels

Nice to have

  • Built security frameworks or libraries adopted across an engineering organization and driven adoption
  • Built or operated zero-trust or BeyondCorp-style access gateway or identity-aware proxy
  • Migrated infrastructure fleet to mTLS at scale including certificate issuance and staged enforcement
  • Maintained or contributed to open-source cryptographic libraries
  • Designed authorization systems using policy languages or relationship-based models
  • Familiarity with ML infrastructure for training and inference serving

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