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Insight Global

San Diego / Global

Security Engineer

Job Description

Our client is seeking a Cloud Security Engineer III – AI/ML Platforms to help design, implement, and mature security across its AWS cloud environment and rapidly growing AI/ML ecosystem. This individual will work across both cloud security engineering and security architecture, partnering with cloud, development, data, and AI/ML teams to build security into systems earlier in the development lifecycle. This is a senior technical role for someone who can operate independently, establish security guardrails, assess vulnerabilities and risk, and translate security requirements into practical solutions for engineering teams. The role will be approximately 50% traditional cloud security and 50% AI/ML-focused security, although deep AI/ML security expertise is not required coming in.

REQUIRED SKILLS AND EXPERIENCE 8+ years of experience across security engineering, cloud security, security architecture, or related security disciplines.

3–5+ years of hands-on AWS cloud security experience, ideally with deeper experience securing enterprise AWS environments.

Strong experience with AWS security services and controls, including IAM, Security Hub, GuardDuty, CloudTrail, KMS, VPC/network security, S3, AWS Organizations, or similar services.

Experience across both security architecture and engineering, including designing security controls, establishing guardrails, assessing risk, and supporting secure cloud implementations.

Experience with enterprise security platforms, firewalls, vulnerability management, threat detection, and remediation.

Understanding of modern cloud engineering practices, including CI/CD pipelines and Infrastructure as Code (IaC).

Ability to operate independently as a security SME and communicate security risks, metrics, and recommendations to both technical teams and leadership.

NICE TO HAVE SKILLS AND EXPERIENCE Exposure to AI/ML platforms or security concepts, including securing data flows, APIs, model access, pipelines, or deployment environments.

Experience with AWS AI/ML services such as Amazon Bedrock and/or SageMaker.

AWS Security, CISSP, GSEC, Security+, AWS Solutions Architect, or other relevant security/cloud certifications.

Experience within a software or technology-driven organization utilizing mature DevSecOps, CI/CD, and IaC practices.

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