Responsibilities
- Manage and lead multiple DevSecOps teams, mentor and hire senior DevSecOps and security engineers, building high-performing teams focused on security excellence across traditional and AI workloads.
- Secure AI/ML pipelines and infrastructure by implementing security controls for model deployment environments, ensuring protection against AI-specific threats such as prompt injection, data poisoning, and model extraction.
- Establish AI security governance frameworks including policies for LLM usage, RAG (Retrieval Augmented Generation) systems security, MCP (Model Context Protocol) security, and AI supply chain risk management.
- Implement automated security scanning for AI artifacts including model files, training datasets, and AI-generated code, integrating these checks into CI/CD pipelines alongside traditional SAST, DAST, and SCA tools.
- Oversee security for AI workload identity and access management, ensuring proper authentication, authorization, and encryption for AI services, APIs, and vector databases used in RAG systems.
- Lead AI security incident response for threats specific to AI/ML systems including adversarial attacks, model theft, data leakage through LLM outputs, and unauthorized AI service usage.
- Ensure adherence to compliance standards such as SOC 2, ISO 27001, SOX, and MRC by automating compliance evidence collection, with special focus on AI governance and responsible AI principles.
- Define and execute DevSecOps strategy aligned with business objectives, security requirements, and emerging AI security best practices across the organization.
- Create architecture designs for security systems and services spanning multiple teams and infrastructure areas, including AI-specific security architectures.
- Drive continuous improvement of security automation, AI security tooling, and processes across traditional and AI workloads.
- Establish security metrics and KPIs to measure team effectiveness, security posture, and AI risk exposure.
- Foster a culture of security awareness and AI security best practices across engineering, data science, and product teams.
- Collaborate with senior/executive management regularly on security strategy, AI risk management, and cross-organizational security initiatives.
Requirements
- 5-6+ years of experience in Cybersecurity/DevOps, or DevSecOps, with proven experience leading security teams of ~5+ engineers across multiple infrastructure areas.
- Leads teams of two or more functional areas with authority over team processes, tools, and priorities; decisions may jeopardize business activities.
- Regularly interacts with senior/executive management, communicating timeline, scope, and technical concerns to all stakeholders.
- Leads Sev1/2 incidents for team's areas of responsibility and provides strategic direction during major security events.
- Exercises supervision over costs, methods, and staffing with responsibility for resource utilization and budget for teams; may have subordinate supervisors or team leads.
- Bachelor's degree in Computer Science, Information Systems, or equivalent experience in a related field.
Team
Team size: 2-5+. Structure: multiple teams
