A position is available for a DevSecOps Engineer to join a team focused on developing secure CI/CD pipelines and integrating Artificial Intelligence (AI) capabilities. This role requires a strong blend of DevOps practices, security principles, and practical experience with implementing AI/ML technologies.

This is a full-time, Regular position with travel required up to 10% (Local). No minimum security clearance is required to start.

Role Summary and AI/Security Mandate

The ideal candidate will be instrumental in bridging the gap between secure, continuous delivery and the emerging field of machine learning operations (MLOps). You will be responsible for designing and automating secure software development lifecycles while ensuring the seamless integration and secure deployment of AI/ML models.

Key Responsibilities:

• Secure CI/CD Pipelines: Design, implement, and maintain secure CI/CD pipelines using tools like GitLab.
• AI/ML Integration: Integrate AI/ML models and tools into existing DevOps processes, including deployment and configuration.
• Security Automation: Develop and implement security measures throughout the SDLC, including automating security testing and vulnerability assessments (SAST, DAST).
• Infrastructure & Containerization: Implement and manage containerization and orchestration technologies (Docker, Kubernetes), utilizing Infrastructure-as-Code (IaC) tools (Terraform, Ansible).
• Monitoring & Optimization: Monitor and optimize system performance and security, including developing and maintaining documentation for processes.
• Collaboration: Collaborate with development teams to ensure best practices in security and AI integration within an Agile environment.

Required Experience and Technical Qualifications

The successful candidate will have a foundational background in IT or software engineering and specific experience spanning cloud, automation, security, and AI implementation.

• Required Qualifications:
  • Bachelor’s degree in Computer Science, Software Engineering, or related field.
  • 3+ years of experience in DevOps or related roles.
  • Strong knowledge of CI/CD tools (e.g., GitLab).
  • Proficiency with Linux/Unix admin and scripting languages (e.g., Python, Bash).
  • Experience with cloud platforms (e.g., OCI, AWS).
  • Experience with containerization technologies (Docker, Kubernetes).
  • Knowledge of security best practices and tools (SAST, DAST).
  • Experience with infrastructure-as-code tools (e.g., Terraform, Ansible).
  • Experience implementing AI technologies.
  • Experience with Agile methodologies.
• Desired Skills (Bonus):
  • Experience with AI/ML model deployment and integration.
  • Knowledge of AI/ML frameworks (TensorFlow, PyTorch, scikit-learn).
  • Familiarity with MLOps practices.
  • Certifications in cloud platforms, security, or DevOps (e.g., AWS Certified DevOps Engineer, CISSP).
  • Experience with monitoring and logging tools (e.g., ELK stack, Prometheus, Grafana, Langfuse).