Senior SecOps Engineer

About Us:

AI71 is an applied research team dedicated to creating helpful and responsible AI agents for knowledge workers. Working closely with our industry partners, our cross-functional teams of AI experts build products grounded in the cutting-edge research of our colleagues from the Technology Innovation Institute (TII). At AI71, we are passionate about transforming industries through the responsible deployment of AI, particularly leveraging Large Language Models (LLMs) to empower businesses. We are looking for a talented SecOps Engineer to join our growing team and help ensure that our AI-driven solutions are secure, compliant, and resilient.

Position Overview: As a SecOps Engineer at AI71, you will play a key role in ensuring the security and operational integrity of our AI-powered solutions, especially those utilizing Large Language Models (LLMs). You will work closely with engineering, DevOps, and product teams to design, implement, and maintain security controls and best practices to protect our AI models, infrastructure, and client data. Your work will be essential in creating secure systems that allow us to deploy and operate LLM-based solutions at scale.

Key Responsibilities:

• Security Monitoring & Incident Response: Develop, implement, and manage security monitoring tools and processes to proactively identify and respond to security threats. Investigate and remediate security incidents, ensuring minimal disruption to operations.
• LLM Security: Collaborate with AI and DevOps teams to ensure that the deployment and operation of LLM-based solutions are secure. This includes managing access controls, securing APIs, and ensuring data privacy and protection for AI models and client data.
• Vulnerability Management: Identify, assess, and mitigate vulnerabilities in both infrastructure and AI models. Ensure timely patching of systems and compliance with security best practices and regulatory requirements.
• Cloud Security: Oversee the security of cloud-based AI infrastructure (AWS, GCP, Azure) to ensure compliance with industry standards and security policies. Implement security measures like encryption, identity and access management (IAM), and network security.
• Security Automation: Automate security processes and workflows, including vulnerability scanning, compliance checks, and incident response. Ensure that security is integrated into CI/CD pipelines.
• Compliance & Governance: Work with legal and compliance teams to ensure that AI deployments meet relevant regulations and standards (e.g., GDPR, HIPAA). Implement and maintain controls to support compliance audits.
• Collaboration & Training: Collaborate with cross-functional teams to incorporate security considerations into AI development, deployment, and operations. Provide training and awareness on security best practices to internal teams.
• Threat Intelligence: Stay informed on emerging security threats, vulnerabilities, and trends in the AI and LLM landscape. Apply threat intelligence to continuously improve security posture.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Cybersecurity, or a related field.
• 3+ years of experience in a SecOps or security engineering role, with a focus on cloud environments and infrastructure security.
• Proven experience securing AI and machine learning systems, particularly those involving large-scale LLMs or NLP models.
• Hands-on experience with cloud platforms (AWS, GCP, Azure) and cloud security best practices.
• Experience with security tools and practices such as SIEM, IDS/IPS, firewalls, encryption, vulnerability management, and incident response.
• Familiarity with compliance frameworks and standards (e.g., GDPR, SOC 2, ISO 27001).
• Strong scripting and automation skills (e.g., Python, Bash, or similar) for security operations tasks.
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes) and securing containerized applications.
• Strong communication skills, with the ability to clearly explain security issues to both technical and non-technical stakeholders.

Preferred Qualifications:

• Experience with securing AI/ML models, including access control, model explainability, and auditing.
• Knowledge of ethical AI practices, data privacy, and the potential risks of AI models.
• Certifications in cybersecurity (e.g., CISSP, AWS Certified Security Specialty, CompTIA Security+).
• Experience with DevSecOps practices and integrating security into the software development lifecycle (SDLC).

Why Join Us:

• Work at the cutting edge of AI, particularly in the rapidly evolving field of LLMs, alongside top-tier AI experts and researchers.
• Contribute to building secure, responsible AI solutions that empower businesses and help knowledge workers.
• Competitive salary and benefits, including flexible work options.
• Access to continuous learning and professional development opportunities.
• Join a collaborative, dynamic, and inclusive culture that values security, innovation, and teamwork.