Senior Security Engineer: AI & DevSecOps

What You'll Be Doing

As a Senior DevSecOps & AI Security Engineer, you'll own the technical implementation of security initiatives across cloud infrastructure, software delivery pipelines, and AI-enabled development environments.

🤖 Secure AI Platforms & Agentic AI

• Design and implement security architectures that enable the safe adoption of Generative AI, AI coding assistants, LLMs, and autonomous AI agents.
• Define and enforce security guardrails for AI systems capable of executing code, accessing enterprise resources, interacting with APIs, and handling sensitive information.
• Assess and mitigate AI-specific risks, including:
• Prompt Injection
• Data Exfiltration
• Model Supply Chain Risks
• AI Agent Abuse
• LLM Security Vulnerabilities
• Sensitive Data Exposure
• Support the secure integration of externally developed AI services and platforms into enterprise environments.
• Collaborate with engineering and data teams to ensure AI solutions are designed with security, privacy, and compliance by default.

☁️ Cloud Security & DevSecOps

• Design, implement, and continuously improve security controls across modern cloud-native infrastructure.
• Embed automated security controls into CI/CD pipelines, Infrastructure as Code (IaC), and software delivery workflows.
• Promote DevSecOps best practices by integrating security into every stage of the software development lifecycle.
• Continuously assess cloud environments to identify vulnerabilities, misconfigurations, and opportunities for security improvement.

🛡️ Security Engineering

• Own and administer enterprise security platforms, ensuring they are correctly configured, monitored, and continuously optimized.
• Implement automated security monitoring, vulnerability management, endpoint protection, cloud security posture management, and zero-trust networking.
• Build internal automation tools that improve operational efficiency and reduce manual security processes.
• Develop security scripts and integrations using Python and other automation technologies.

Protect Modern Development Environments

• Secure developer platforms, CI/CD pipelines, source code repositories, build systems, and internal engineering tooling.
• Define least-privilege access models for cloud resources, AI systems, and development environments.
• Strengthen identity, authentication, authorization, and audit capabilities across engineering platforms.
• Ensure traceability, logging, and security monitoring for AI workloads and cloud-native applications.

🤝 Collaboration & Security Leadership

• Partner with Software Engineers, DevOps Engineers, Platform Teams, Data Scientists, Architects, and Security professionals to build secure engineering practices.
• Translate governance and compliance requirements into practical, automated technical controls.
• Support security reviews, architecture discussions, and technology evaluations from a security engineering perspective.
• Represent the technical security function during internal and external audits by presenting security controls, technical evidence, and implementation practices.
• Champion a security-first engineering culture without compromising developer productivity or innovation.

🛠️ What We're Looking For

Required Experience

✔️ Strong background in Software Engineering, Platform Engineering, DevOps, or Cloud Engineering, followed by experience in Cybersecurity or Security Engineering.

✔️ Hands-on experience securing modern cloud-native infrastructure and containerized environments.

✔️ Experience implementing DevSecOps practices and integrating security into CI/CD pipelines.

✔️ Strong understanding of Infrastructure as Code (IaC) and cloud automation principles.

✔️ Experience administering enterprise security platforms covering areas such as:

• Cloud Security Posture Management (CNAPP)
• Endpoint Detection & Response (EDR)
• Security Information & Event Management (SIEM)
• Zero Trust Networking

✔️ Strong scripting and automation skills using Python.

✔️ Excellent communication skills with the ability to collaborate across engineering, security, and business teams.

Technical Stack

Security

• Cloud Security
• DevSecOps
• Zero Trust Architecture
• Vulnerability Management
• Identity & Access Management (IAM)
• Least Privilege
• Security Automation
• Security Monitoring
• Threat Detection
• Compliance & Audit

AI Security

• Generative AI
• Agentic AI
• Large Language Models (LLMs)
• AI Coding Assistants
• AI Governance
• Prompt Injection Mitigation
• AI Supply Chain Security
• Secure AI Adoption

Cloud & Infrastructure

• Cloud-Native Applications
• Containers
• Kubernetes
• Infrastructure as Code (IaC)
• CI/CD Pipelines

Automation

• Python
• Security Automation
• Infrastructure Automation

Security Platforms (Ideally)

• Wiz
• CrowdStrike
• Google SecOps
• Tailscale

⭐ Nice to Have

➕ Experience securing AI workloads, machine learning platforms, or enterprise data pipelines.

➕ Knowledge of container security and Kubernetes security best practices.

➕ Experience implementing cloud-native security architectures.

➕ Familiarity with secure software supply chain practices (SBOM, SAST, DAST, dependency scanning, secrets management).

➕ Experience working in highly regulated industries where security, privacy, and compliance are business-critical.