AI Security Engineer
Listed on 2026-08-02
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IT/Tech
Cybersecurity, AI Engineer (Applied/Software), Information Security & Data Protection
About Us:
Structure Therapeutics develops life‑changing medicines for patients using advanced structure‑based and computational drug discovery technology. The company’s platform combines the latest advancements in visualization of molecular interactions, computational chemistry, and data integration to design orally available, superior small molecule medicines that overcome current limitations of biologic and peptide drugs. We are advancing a clinical‑stage pipeline of differentiated treatments focused on chronic diseases with high unmet need, including cardiovascular, metabolic, and pulmonary conditions.
Structure Therapeutics is led by an experienced group of international drug innovators and financed by top‑tier global life sciences investors. The company completed an initial public offering (IPO) in February 2023. With offices in California and Shanghai, Structure Therapeutics has the benefit of being at the center of life science innovation in both the US and China and capitalizing on the strengths of each geographic location.
Position Summary:
The AI Security Engineer will be a key member of the “Structure Brain” initiative, responsible for designing, implementing, and maintaining security measures for our AI/ML platform on AWS. This role will focus on securing AI models, data pipelines, and infrastructure while contributing to the development of AI governance and security policies.
The ideal candidate will have a strong background in cybersecurity, experience with AI/ML systems, and expertise in cloud security, particularly within AWS environments.
As part of our new “Structure Brain” initiative, we are building an AI/ML platform on AWS to drive cutting‑edge solutions in biotechnology. We are seeking an AI Security Engineer to join our team and ensure the security and governance of our AI systems.
Job Responsibilities:
- AI/ML Security Design and Implementation:
- Develop and implement security controls for AI/ML models, including data protection, model integrity, and adversarial attack mitigation.
- Secure data pipelines and ensure compliance with data privacy regulations (e.g., GDPR, HIPAA).
- Integrate security best practices into AI/ML workflows, including secure model training and deployment.
- Cloud Security:
- Design and maintain secure AWS architectures for AI/ML workloads, leveraging services like AWS Sage Maker, Lambda, and S3.
- Implement identity and access management (IAM) policies, encryption, and network security controls in AWS.
- Monitor and respond to security incidents within the AI/ML platform.
- AI Governance and Policy Development:
- Collaborate with the Director of Security and Compliance to develop AI governance frameworks, including ethical AI use and risk management.
- Create and enforce security policies for AI systems, ensuring alignment with industry standards and regulatory requirements.
- Conduct risk assessments and audits of AI/ML systems to identify and mitigate vulnerabilities.
- Collaboration and Support:
- Work closely with Data Engineers, ML Engineers, and Dev Ops Engineers to embed security into the AI/ML development lifecycle.
- Provide guidance and training to team members on AI security best practices.
- Support the Technical Project Manager in ensuring security milestones are met within project timelines.
- Threat Monitoring and Incident Response:
- Monitor AI/ML systems for potential threats, including adversarial AI attacks and data breaches.
- Develop and execute incident response plans specific to AI/ML environments.
- Stay updated on emerging AI security threats and incorporate proactive measures.
Qualifications:
- Bachelor’s degree in Computer Science, Cybersecurity, Information Technology, or a related field. Master’s degree preferred.
- 5+ years of experience in cybersecurity, with at least 2 years focused on securing AI/ML systems or cloud-based environments.
- Hands‑on experience with AWS security tools and services (e.g., AWS IAM, KMS, Cloud Trail, Guard Duty).
- Familiarity with AI/ML frameworks (e.g., Tensor Flow, PyTorch) and their security implications.
- Experience developing or implementing security policies and governance frameworks.
- Knowledge of data privacy regulations (e.g., GDPR, HIPAA) and their…
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