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CuspAI

AI system designs candidate materials

Security Engineer

Security Engineering & ArchitectureConfirmed live in the last 24 hours
Full-timeHybrid

About the Job

Requirements

  • At least 3 years of experience in a DevSecOps, Cloud Security, or Site Reliability Engineering role, preferably within a fast-paced startup or AI-centric company.
  • Proven experience building and securing CI/CD pipelines, such as GitHub Actions, GitLab CI, or Jenkins.
  • Strong proficiency in Infrastructure as Code, such as Terraform or Pulumi, and securing cloud environments such as AWS, GCP, or Azure.
  • Deep understanding of container security and orchestration, including Docker and Kubernetes.
  • Practical knowledge of security frameworks and how to implement them without slowing development cycles.

Responsibilities

  • Secure the end-to-end machine learning lifecycle by implementing defenses against data poisoning and protecting proprietary model weights from theft.
  • Design and deploy prompt-injection defenses and runtime firewalls to prevent unauthorized manipulation of large language model interfaces.
  • Implement AI Security Posture Management to monitor and catalog self-hosted models, internal training datasets, and proprietary endpoints.
  • Integrate automated security guardrails into CI/CD workflows, including secret scanning, API exposure checks, and software composition analysis.
  • Codify security policies using Infrastructure as Code to ensure cloud resources comply with standards such as GDPR and SOC 2.
  • Manage secrets and vulnerability patching for containerized environments such as Docker and Kubernetes.
  • Design least-privilege Identity and Access Management controls to isolate sensitive training data and research workloads.
  • Lead incident response by monitoring production logs for anomalies and collaborating with AI researchers to deploy rapid fixes.
  • Provide tools for local integrated development environment security scanning and pre-commit hooks to help the engineering team own security.
  • Cultivate a shared-responsibility security culture across AI, chemistry, and engineering teams.
  • Partner with researchers, chemists, and engineers to translate security requirements into practical workflows that support scientific work.

Desired Qualifications

  • Direct experience with AI-specific security tools or defending against large language model-specific vulnerabilities, such as the OWASP Top 10 for LLMs.
  • Experience with AI Security Posture Management tools.
  • Relevant certifications such as AWS Certified Security, CSEP, or OSCP.
  • A background or personal interest in materials science, chemistry, or the intersection of AI and physical sciences.

About the Company

CuspAI

AI system designs candidate materials

CuspAI builds an AI system for materials discovery that acts like a search engine for materials that do not yet exist. Its AI Materials Foundry uses a global network of labs, computing resources, and partners to design candidate materials when customers specify desired properties, spanning semiconductors, energy, climate, water treatment, and carbon capture. Unlike others, it combines AI-driven materials design with a broad, real-world Foundry network and high-profile advisers to turn requests into tangible material candidates. The company’s goal is to accelerate the creation of new materials by providing a scalable, end-to-end workflow that goes from property targets to candidate materials ready for testing and development, with ongoing expansion across the US, APAC, and Europe.

Company size
51-200
Company stage
Series B
Total funding
$580M
Headquarters
Cambridge, United Kingdom
Founded
2024

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