SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Aidoc is the market leader in healthcare AI, operating the world's largest clinical frontier model that supports nearly 50 million patients annually across 2,000+ medical centers globally. The company has raised over $500 million since 2016 and holds a record number of FDA-cleared solutions.
As a Senior Security Engineer, you will be a hands-on technical contributor responsible for embedding security into Aidoc's products, platforms, AI systems, and clinical workflows. This role bridges product security, cloud infrastructure, and healthcare-specific challenges in a regulated, high-impact environment.
Key responsibilities include:
- Secure product and clinical workflows end-to-end by identifying, prioritizing, and remediating security risks across services, APIs, medical imaging workflows, AI outputs, and data flows.
- Drive secure-by-design architecture by providing guidance on authentication, authorization, tenant isolation, encryption, secrets management, and audit logging.
- Strengthen cloud-native security across cloud environments, Kubernetes, containers, IAM, network segmentation, and infrastructure-as-code.
- Embed security into the development lifecycle by integrating and operationalizing security tooling across CI/CD pipelines (SAST, SCA, IaC scanning, container scanning, secrets detection).
- Own vulnerability management as an engineering system, prioritizing based on exploitability, product exposure, customer impact, and clinical risk.
- Secure AI/ML-driven features and data pipelines by partnering with AI and data teams to identify risks related to training/inference data, model inputs/outputs, and data leakage.
- Improve software supply-chain security across open-source dependencies, third-party components, container images, and deployment processes.
- Mentor and enable engineering teams to build security into their workflows.
This role is unique because security decisions directly affect clinical workflows, patient safety, and care-team coordination. You will work with highly sensitive healthcare data (medical imaging, PHI/PII, clinical metadata) in a complex ecosystem integrating with hospital systems (PACS, EHR, VNA, RIS, scheduling systems). The role extends beyond traditional application security into AI/ML security, medical imaging system protection, and inference integrity—all within a regulated healthcare environment where security must be practical, evidence-based, and aligned with regulatory expectations.
