2 месяца назад
Security Engineering Manager (AI/Cybersecurity)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Security Engineering Manager (AI/Cybersecurity): Building and leading security engineering for a digital biology platform, with an accent on cloud security, AI-first architecture, and secure ML environments. Focus on defining the security roadmap, securing GCP and Kubernetes workloads, automating security posture management, and resolving complex incidents and architectural vulnerabilities.
Location: London, United Kingdom or Lausanne, Switzerland. Hybrid working with three days per week in the office required.
Company
applies AI and machine learning to drug discovery and digital biology, building predictive and generative models based on and beyond AlphaFold.
What you will do
- Lead, mentor, and scale a high-performing security engineering team.
- Define and implement the technical security roadmap covering IAM, cloud and network security, secure SDLC, and security monitoring.
- Oversee security for cloud infrastructure, platforms, containerized workloads, and AI-enabled security automation.
- Lead security transformation projects supporting frontier ML models and new therapeutics.
- Develop KPI-driven security programs and communicate progress and risks to executive management.
- Act as the senior escalation point for complex incidents, architectural vulnerabilities, and high-stakes risk remediation.
Requirements
- Experience managing, building, or leading technical security teams in scale-ups, startups, or major technology organizations.
- Deep experience designing and implementing security architectures for complex, multi-tenant cloud systems.
- Professional exposure to security, regulatory, and architectural challenges in AI/ML or life sciences.
- Strong experience securing cloud platforms, preferably GCP, containerized workloads using Kubernetes and Docker, and Zero Trust frameworks.
- Ability to balance strategic risk planning with hands-on technical implementation and business priorities.
- Excellent communication skills for explaining technical vulnerabilities and architectural risks to executives and non-security stakeholders.
Nice to have
- Experience securing ML training lifecycles, proprietary model weights, or autonomous workflow guardrails.
- Knowledge of ISO 27001, ISO 42001, GxP, FDA requirements, or the EU AI Act.
- Proficiency in Python or Go, Terraform, CI/CD security tooling, and cloud-native security controls.
- Professional cloud security certifications or credentials such as CISSP, CISM, or OSCP.
Culture & Benefits
- Collaborative, interdisciplinary environment spanning drug discovery, machine learning, and security engineering.
- Values centered on thoughtful science, initiative, integrity, determination, and cross-functional collaboration.
- Hybrid working model designed to support knowledge sharing and in-person relationships.
- Commitment to equal employment opportunities and reasonable accommodations for additional needs.
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