AI Security Engineer

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 SageMaker, 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 DevOps 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, CloudTrail, GuardDuty).
  • Familiarity with AI/ML frameworks (e.g., TensorFlow, 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 application to AI systems.
• Certifications (Preferred):
  • AWS Certified Security - Specialty
  • Certified Ethical Hacker (CEH)
  • Certified AI Practitioner (CertNexus) or equivalent AI-focused certification
• Technical Skills:
  • Proficiency in securing cloud environments, particularly AWS.
  • Experience with secure coding practices and vulnerability management.
  • Knowledge of AI-specific security risks, such as model inversion, data poisoning, and adversarial attacks.
  • Familiarity with Linux-based systems and scripting (e.g., Python, Bash).
  • Understanding of DevOps practices and tools (e.g., Docker, Kubernetes, CI/CD pipelines).

• Experience in the BioTech or healthcare industry, with knowledge of regulatory compliance (e.g., FDA, HIPAA).
• Familiarity with AI ethics and governance frameworks.
• Prior experience working on large-scale AI/ML projects in a cloud environment.

Travel:

• Remote employees will need to be present for monthly connection weeks, company meetings and/or industry conferences.

Location

Structure Therapeutics has a strong preference for candidates based in the San Francisco Bay Area who are able to work a hybrid schedule from the company's office. The role is expected to require regular in-office presence to support close collaboration with cross-functional teams, executive leadership, and external partners. Candidates outside the Bay Area may be considered in exceptional cases, but the ability to work effectively on a hybrid basis in the San Francisco office is strongly preferred.

Structure Therapeutics is committed to fair and equitable compensation practices, and we strive to provide employees with total compensation packages that are market competitive. For this role, the anticipated base pay range is $147,000-$184,800. The exact base pay offered for this role will depend on various factors, including but not limited to the candidate's geography, qualifications, skills, and experience.

At Structure, base pay is only one part of your total compensation package. The successful candidate will be eligible for an annual performance incentive bonus, new hire equity, and ongoing performance-based equity. Structure Therapeutics also offers various benefits offerings, including, but not limited to, medical, dental, and vision insurance, 401k match, unlimited PTO, and a number of paid holidays including winter shutdown.

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