Cloud Security Engineer

We are looking for a highly skilled Cloud Security Engineer who can embed security across cloud infrastructure, CI/CD pipelines, applications, and AI-enabled environments. This role is ideal for someone with deep hands-on experience in cloud security, automation, and secure software delivery, combined with growing or strong specialization in AI/ML security, LLM security, and modern data platform protection.
The ideal candidate will help design, implement, and scale security controls across our cloud-native ecosystem while partnering closely with engineering, platform, data, and AI teams to ensure security is built into every stage of development and deployment.
Job responsibilities
Design, implement, and manage security controls across cloud environments such as AWS, Azure, or GCP
Secure cloud infrastructure, Kubernetes clusters, containers, storage, networking, IAM, and secrets management
Define and enforce cloud security baselines, guardrails, and best practices using infrastructure-as-code and policy-as-code
Monitor cloud environments for misconfigurations, threats, and anomalous behavior, and drive remediation efforts
Support incident response, threat detection, vulnerability management, and post-incident reviews for cloud systems
Integrate security into CI/CD pipelines and software delivery processes
Implement automated security testing such as SAST, DAST, SCA, container scanning, IaC scanning, and secrets detection
Partner with engineering teams to improve secure SDLC practices and reduce security friction
Build reusable security automation and self-service controls for developers and platform teams
Collaborate with DevOps, SRE, and engineering teams to harden deployment pipelines and production environments
Partner with AI and data teams to secure AI/ML workflows, model development, and deployment pipelines
Define security controls for LLM applications, training data, vector databases, APIs, model endpoints, and agent-based systems
Help assess and mitigate AI-specific risks such as prompt injection, model abuse, sensitive data leakage, insecure plugins/tools, supply chain risks, and unauthorized model access.