Security Engineer III (Cloud, AI / ML-Enhanced Container Security)
Years of Experience : 6- 10 Years
Location : Gurgaon
Industry Type : Cybersecurity / Cloud Engineering / Container Orchestration
Job Summary :
We are seeking a highly specialized Security Engineer III with 6- 9 years of experience, possessing a strong focus on advanced Cloud Security and practical application of AI / ML techniques for enhanced defense, particularly within containerized environments (Kubernetes / Docker).
This critical engineering role requires deep practical experience with major cloud platforms and their native security services. The engineer will be responsible for building, deploying, and maintaining scalable security models, integrating threat detection algorithms into the CI / CD pipeline and container runtime to ensure cutting-edge defense and automated response.
Job Description :
Container and Cloud Security Architecture :
- Design, implement, and maintain robust security controls across major cloud platforms (AWS, Azure, and Google Cloud), focusing on services like IAM, encryption, and network access controls.
- Act as the subject matter expert for Kubernetes and container security, implementing best practices for image scanning, runtime protection, and network segmentation within the orchestration layer.
- Secure the entire container lifecycle (CI / CD), including vulnerability scanning during build (image signing) and implementing admission controllers for deployment governance.
- Deploy and configure cloud-native security tools that utilize AI / ML for container threat detection (e.g., AWS GuardDuty, Azure Sentinel, or specialized third-party tools like Falco or Twistlock), ensuring optimal tuning.
AI / ML Security Model Development and Integration :
Apply hands-on experience with AI / ML techniques for advanced cybersecurity applications, including supervised and unsupervised learning, specifically focusing on anomaly detection within container logs and application behavior.Develop, train, and deploy security models in automated, scalable environments, integrating them seamlessly into the CI / CD pipeline and runtime monitoring stack.Demonstrate proficiency in essential programming and scripting languages (Python, R) and mandatory experience with TensorFlow, Keras, or similar AI / ML tools for building and validating models.Utilize insights from AI / ML models to dynamically enhance traditional perimeter security and micro-segmentation policies within the container network.Threat Management and Incident Response :
Leverage expertise in threat intelligence and vulnerability management to proactively identify, assess, and prioritize risks within the cloud and container infrastructure.Participate actively in the incident response framework, utilizing analytical skills and AI / ML insights to accelerate threat classification, containment, and root cause analysis in container break-out scenarios.Ensure all deployed security solutions meet high performance, scalability, and compliance requirements.Required Skills & Expertise :
Container Security : Mandatory expertise in Kubernetes and container security, including image scanning, runtime protection, and network policy enforcement.Cloud Platforms : Practical experience with security services across AWS, Azure, and Google Cloud (e.g., IAM, encryption, Security Groups).AI / ML Cyber : Hands-on experience with AI / ML techniques for cybersecurity (e.g., supervised / unsupervised learning, anomaly detection, threat classification).Programming : Proficiency in Python (or R) and experience with core AI / ML frameworks (TensorFlow, Keras, or similar).Automation : Experience in building and deploying security models in automated, scalable environments (MLOps principles) and integrating security into the CI / CD pipeline.Security Tools : Familiarity with cloud-native / specialized security tools for containers (e.g., AWS GuardDuty, Falco, Azure Sentinel).G&C : Experience with threat intelligence, vulnerability management, and incident response frameworks.(ref : hirist.tech)