Rhino Partners is seeking a hands-on DevSecOps & AI Security Engineer to design, implement and maintain secure development pipelines, infrastructure and application environments.
The ideal candidate will have a strong foundation in DevSecOps, cloud/platform engineering and application security, with an interest in applying security engineering practices to AI/LLM technologies.
Key Responsibilities- Design, implement and maintain secure CI/CD pipelines, integrating automated security checks throughout the software development lifecycle.
- Implement and manage infrastructure-as-code, containerised environments and deployment automation.
- Integrate application security testing, vulnerability scanning and security controls into development and deployment workflows.
- Conduct vulnerability assessments, system hardening, remediation and security configuration reviews across infrastructure and applications.
- Implement security-by-design principles and secure software development practices across engineering teams.
- Configure and maintain logging, monitoring, alerting and security observability solutions across development pipelines and runtime environments.
- Support the security and maintenance of on-premise, cloud and containerised infrastructure.
- Automate security processes, compliance checks and vulnerability management workflows.
- Collaborate with software engineers, platform teams and cybersecurity stakeholders to identify and remediate security risks.
- Support the evaluation and implementation of security controls for AI/LLM applications, including AI testing, guardrails and protection mechanisms.
Requirements- 3–7 years of relevant experience in DevSecOps, software engineering, cloud/platform engineering or cybersecurity engineering.
- Strong hands-on experience building and maintaining CI/CD pipelines and deployment automation.
- Practical experience with infrastructure-as-code tools, containerisation and modern DevSecOps toolchains.
- Familiarity with Docker, Kubernetes and on-premise or cloud infrastructure environments.
- Strong understanding of secure software development, application security, vulnerability management and security-by-design principles.
- Experience implementing security controls, vulnerability scanning, system hardening and remediation.
- Experience configuring logging, monitoring and security controls across development pipelines and runtime environments.
- Strong troubleshooting, scripting and automation skills.
Good to Have- Exposure to AI/LLM applications, AI security risks, AI evaluation tools or AI guardrails.
- Experience with security tools such as SAST, DAST, software composition analysis and container security scanning.
- Familiarity with cloud security practices across AWS, Azure or other enterprise environments.
- Relevant certifications such as CISSP, CCSP, AWS/Azure Security, CKA, CKS, GIAC or CREST.
Candidates who combine hands-on DevSecOps and cybersecurity engineering experience with practical exposure to AI/LLM technologies or AI security will be highly regarded.