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 responsibilitiesDesign, implement, and manage security controls across cloud environments such as AWS, Azure, or GCPSecure cloud infrastructure, Kubernetes clusters, containers, storage, networking, IAM, and secrets managementDefine and enforce cloud security baselines, guardrails, and best practices using infrastructure-as-code and policy-as-codeMonitor cloud environments for misconfigurations, threats, and anomalous behavior, and drive remediation effortsSupport incident response, threat detection, vulnerability management, and post-incident reviews for cloud systemsIntegrate security into CI/CD pipelines and software delivery processesImplement automated security testing such as SAST, DAST, SCA, container scanning, IaC scanning, and secrets detectionPartner with engineering teams to improve secure SDLC practices and reduce security frictionBuild reusable security automation and self-service controls for developers and platform teamsCollaborate with DevOps, SRE, and engineering teams to harden deployment pipelines and production environmentsPartner with AI and data teams to secure AI/ML workflows, model development, and deployment pipelinesDefine security controls for LLM applications, training data, vector databases, APIs, model endpoints, and agent-based systemsHelp 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.Requirements: Bachelors degree in Computer Science, Cybersecurity, Information Security, or a related field, or equivalent practical experience3+ years of experience in cloud security, DevSecOps, application security, or infrastructure security rolesStrong hands-on experience with at least one major cloud platform: AWS, Azure, or GCPPractical experience with containers, Kubernetes, Terraform, and CI/CD tools such as GitHub Actions, GitLab CI, Jenkins, or similarStrong understanding of security engineering principles including IAM, network security, encryption, logging, secrets management, and vulnerability managementExperience implementing security tooling in engineering workflowsScripting or coding experience in Python, Bash, or GoStrong communication skills and ability to work cross-functionally with engineering and platform teamsPreferred Qualifications:Experience securing AI/ML platforms, MLOps pipelines, or LLM-based applicationsFamiliarity with AI security topics such as prompt injection, model security, data poisoning, adversarial ML, privacy risks, and AI governanceExperience with security in cloud-native architectures, microservices, and distributed systemsExperience with SIEM, CSPM, CNAPP, EDR, or cloud workload protection platformsRelevant certifications such as:AWS Security SpecialtyGoogle Professional Cloud Security EngineerCISSP, CCSP, or Kubernetes security certificationsTechnical SkillsCloud platforms: AWS / Azure / GCPDevSecOps tools: SAST, DAST, SCA, IaC scanning, container scanningInfrastructure and orchestration: Terraform, Docker, KubernetesCI/CD: GitHub Actions, GitLab, Jenkins, ArgoCDSecurity concepts: IAM, zero trust, secrets management, encryption, logging, incident responseThis position is open to all candidates.