About Aidoc

Aidoc is the market leader in healthcare AI and has developed the world's largest clinical frontier model, supporting nearly 50 million patients each year.

Aidoc is deployed in more than 2,000 medical centers worldwide. Since our founding in 2016, Aidoc has raised over $500 million and achieved a record number of FDA-cleared solutions.

Medical diagnosis is hitting a breaking point, where the number of physicians hasn't kept up with the rapidly growing patient load. This leads to misdiagnosis and treatment delays that result in hundreds of thousands of deaths every year. Aidoc assists clinicians by precisely highlighting diseases directly on medical images, preventing misdiagnosis and ensuring that urgent patients receive the immediate attention they need.

Senior Cloud Security Engineer

Join our existing R&D Security team as Aidoc's first dedicated Cloud Security Engineer. You will shape cloud security standards, assess attack paths across AWS and Kubernetes, and turn findings into adopted controls with DevOps and workload owners. This is a hands-on role in security assessment, automation and verification, working alongside security leadership and SecOps.

We run AWS services, use Terraform and AWS CDK, and build through CI. Cloud security scanners provide AWS configuration visibility; runtime coverage across our compute environments needs assessment and expansion. Our scope also includes cloud connections to Aidoc applications deployed inside hospital networks.

Responsibilities

Assess AWS architecture and attack paths involving IAM role trust and permissions, networking, storage, encryption and secrets access. Recommend baselines and help engineering adopt controls appropriate to the workload.
Review Kubernetes security across access to the Kubernetes API, AWS access for workloads, admission controls, container settings and network isolation. Validate that controls work in the deployed environment.
Assess EC2 host and workload security and Lambda function security, including credential access and data protection. Review Lambda execution-role permissions and permissions to invoke functions as separate controls.
Review Terraform and AWS CDK changes, build preventive checks in CI, and verify deployed controls. Develop security automation in Python or shell and reusable guidance with infrastructure owners.
Assess cloud security scanner coverage and finding quality, validate exposures using configuration and runtime evidence, and define improvements with SecOps and DevOps. Drive agreed remediation and verify risk reduction.
Assess cloud-side access and connectivity for Aidoc applications in hospitals with AppSec, product teams and hospital IT. Help plan appropriate visibility for these deployments.
Plan control validation with engineering around clinical service availability. Track control adoption and recurring risks, support SecOps investigations, and provide technical evidence to Quality and Regulatory partners.

Requirements

5+ years of relevant experience in Cloud Security, Infrastructure Security, DevSecOps, DevOps or SRE, including hands-on production security improvements.
Built or substantially improved a cloud security practice: assessed risks, improved controls and coverage, gained engineering adoption, and verified remediation.
Strong practical AWS security across IAM, networking, storage, encryption, logging and workload access; ability to investigate and explain attack paths.
Hands-on production Kubernetes security experience, with sound Linux and networking fundamentals and an understanding of EC2 and serverless security boundaries.
Ability to review infrastructure as code in Terraform or AWS CDK, transfer that knowledge to the other framework, and build security automation and CI checks in Python or shell.
Clear communication in English and practical judgment about testing, staged rollout, rollback and verification of security changes.

Useful additional experience

Experience using cloud security scanners, Wiz, Upwind or comparable cloud and runtime security platforms to improve coverage and validate findings.