About The Position

This role operates at the cutting edge of frontier security engineering. You will spearhead our transition into Post-Quantum Cryptography (PQC), architect advanced privacy-preserving runtimes, implement real-time kernel-level observability, and construct highly secure AI/LLM inference pipelines.

Requirements

  • Direct, demonstrable experience in Advanced Cryptography: Production-grade implementation of Homomorphic Encryption, Secure Multi-party Computation (SMPC), and Zero Knowledge Proofs (ZKP).
  • Direct, demonstrable experience in Kernel & Runtime Defense: Deep expertise in eBPF Security Monitoring and Runtime Application Self-Protection (RASP) frameworks.
  • 10+ years of progressive experience in enterprise cybersecurity architecture and infrastructure engineering.
  • Proven track record designing and implementing Post-Quantum Cryptography (PQC) strategies alongside robust crypto-agility frameworks.
  • Hands-on mastery of hardware-level Confidential Computing using Trusted Execution Environments (TEEs).
  • Experience deploying Identity Threat Detection & Response (ITDR) solutions and establishing workload identities with SPIFFE/SPIRE for service-to-service authentication.
  • Hardened experience protecting live AI inference pipelines built on TensorRT-LLM and Triton Inference Server.
  • Extensive familiarity managing Kubernetes-native security policies via Kyverno to guarantee multi-cluster policy-as-code enforcement.
  • Experience embedding security guardrails natively into developer workflows utilizing Backstage IDP.
  • Ability to design security structures that remain strictly aligned with enterprise FinOps principles.

Responsibilities

  • Formulate and roll out enterprise-wide, future-proofed cryptographic standards resilient against quantum threats.
  • Architect systems using SMPC, Homomorphic Encryption, and ZKPs to protect multi-tenant enterprise workflows.
  • Oversee deployment of eBPF-based security monitoring tools and RASP configurations to track and prevent active zero-day runtime exploits.
  • Partner with AI/ML infrastructure squads to guarantee total data isolation and isolation boundaries for foundational large language models.
  • Sync with risk management, platform infrastructure, and compliance leads to ensure alignment with standard threat modeling frameworks (STRIDE, MITRE ATT&CK).
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