AI71 at the Technology Innovation Institute is seeking a talented SecOps Engineer to join our applied research team focused on creating secure and responsible AI agents for knowledge workers. This role involves ensuring the security and operational integrity of AI-powered solutions, particularly those utilizing Large Language Models (LLMs). You will collaborate closely with engineering, DevOps, and product teams to design, implement, and maintain security controls and best practices that protect our AI models, infrastructure, and client data.
Location: Abu Dhabi Emirate, United Arab Emirates
Work Conditions: On-site, Full-time
Key Responsibilities:
- Develop and manage security monitoring tools and processes to proactively identify and respond to threats.
- Collaborate with AI and DevOps teams to secure the deployment of LLM-based solutions, including managing access controls and securing APIs.
- Identify, assess, and mitigate vulnerabilities in infrastructure and AI models to ensure compliance with security best practices.
- Oversee the security of cloud-based AI infrastructure (AWS, GCP, Azure) and implement necessary security measures.
- Automate security processes and workflows, integrating security into CI/CD pipelines.
- Ensure AI deployments meet relevant regulations and standards, working with legal and compliance teams.
- Provide training and raise awareness about security best practices to internal teams.
- Stay informed about emerging security threats and trends in the AI and LLM landscape.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Cybersecurity, or a related field.
- 3+ years of experience in SecOps or security engineering, with a focus on cloud environments and infrastructure security.
- Proven experience securing AI and machine learning systems, particularly involving LLMs.
- Hands-on experience with cloud platforms (AWS, GCP, Azure) and security best practices.
- Familiarity with compliance frameworks (e.g., GDPR, SOC 2, ISO 27001) and strong scripting skills (e.g., Python, Bash).
- Experience with security tools (e.g., SIEM, IDS/IPS) and containerization tools (e.g., Docker, Kubernetes).
Preferred Qualifications:
- Experience with securing AI/ML models, including access control and auditing.
- Knowledge of ethical AI practices and data privacy.
- Relevant cybersecurity certifications (e.g., CISSP, AWS Certified Security Specialty).
Why Join Us:
- Work at the cutting edge of AI, contributing to secure and responsible AI solutions.
- Competitive salary and benefits with flexible work options.
- Access to continuous learning and professional development opportunities.
- Join a collaborative, dynamic, and inclusive culture that values security, innovation, and teamwork.
