דרושים » אבטחת מידע וסייבר » Senior SecOps Engineer

We are looking for an Application Security Engineer to join our Security Engineering team.

You will take ownership of strengthening security across our products, services, and development lifecycle. This includes identifying and addressing security gaps in application architecture and code, APIs and service-to-service communication, authentication and authorization flows, open source dependencies and third-party libraries, CI/CD pipelines and build systems, secrets handling, and AI-powered product features.

As a Security Engineer, you will dig into how our systems actually work, understand where the real risk is, and decide what needs to be built to close it. Some problems are solved by changing an architecture or a design pattern, others by implementing a new control, embedding a security gate into the pipeline, integrating and tailoring a security platform, or writing something from scratch. You will own that decision and the implementation that follows.

The Security Engineering team works as a group of all-rounders. Alongside your core focus, you will contribute to cloud and infrastructure security, corporate IT security, detection engineering, incident response, and our growing AI security work, both securing AI workloads and using AI to make our own security capabilities better.

What You Will Work On
Identify security gaps across our applications, services, and development lifecycle, then translate them into practical technical solutions.
Design and implement scalable security controls that address root causes and fit our architecture and engineering practices.
Review architectures and designs, run threat modeling, and guide R&D teams toward secure patterns before code is written.
Secure APIs, authentication and authorization flows, service-to-service trust, data handling, and multi-tenant boundaries.
Own the secure development lifecycle end to end, including security gates in GitHub Actions, SAST, SCA, secrets scanning, and dependency and supply chain risk.
Build reusable security capabilities, libraries, paved-road patterns, and developer-facing tooling that make the secure path the default path.
Build custom AI agents and AI-powered capabilities that improve our security tools, workflows, visibility, and control.

we are looking for a Senior Security Engineer.
As a Senior Product Security Engineer, you will help ensure that security is built into the products, platforms, AI systems, and clinical workflows that support healthcare providers and patients at scale. This is a hands-on technical role focused on securing real systems in production, influencing architecture, and partnering closely with engineering, AI, DevOps, product, quality and regulatory.
You will work across cloud-native services, medical imaging workflows, healthcare integrations, AI/ML pipelines, APIs, data flows, and regulated product development processes. Your work will directly support ability to deliver secure, reliable, and trusted clinical AI solutions to healthcare organizations worldwide.
What Makes This Role Unique :
Clinical AI with real-world patient impact - we operate in an environment where security is not only about protecting systems and data. Security decisions can affect clinical workflows, care-team coordination, customer trust, and patient safety.
Highly sensitive healthcare data - You will help protect medical imaging data, clinical metadata, PHI/PII, customer environments, and AI-driven workflows that require strong privacy, access control, data protection, and auditability.
Security for AI/ML and medical imaging systems - The role extends beyond traditional AppSec into AI/ML security, data pipeline protection, inference integrity, model-related risks, and misuse scenarios in clinical workflows.
Complex healthcare integrations - we integrates with hospital systems and healthcare workflows that may include PACS, EHR, VNA, RIS/worklists, scheduling systems, and communication platforms. You will help secure the data flows, authentication models, APIs, and deployment patterns behind these integrations.
Engineering-driven security in a regulated environment - This is not a checkbox compliance role. However, because operates in healthcare and clinical AI, security must be practical, evidence-based, and aligned with regulatory, customer, and quality expectations.
Cloud-native scale and production ownership - You will work with modern cloud infrastructure, Kubernetes, containers, CI/CD pipelines, identity and access management, observability, vulnerability management, and software supply-chain controls.

We are seeking an experienced Data Protection Lead to join the Cyber Security organization.

This role combines hands-on Data Leakage Prevention (DLP) engineering with Data Security Posture Management (DSPM) to deliver end-to-end data protection across corporate, cloud, and SaaS environments. You will not only define strategy and standards - you will build, configure, tune, and operate the technical controls that enforce them.

You will own the data protection lifecycle from discovery and classification through policy enforcement and incident response. The role requires deep technical proficiency in DLP platforms and DSPM tooling, combined with the ability to collaborate with Security, IT, Engineering, Product, Privacy and GRC teams to reduce data exposure risks and embed strong data governance practices.

Your responsibilities will include:
Lead and own the organizations data protection domain, including strategy, standards, and hands-on technical implementation
Engineer, deploy, and continuously tune DLP policies across endpoints, email, SaaS, network proxies, and cloud platforms - covering both inline and API-based enforcement modes.
Design and implement DSPM solutions to gain continuous visibility into sensitive data posture, data flows, misconfigurations, and exposure risks across cloud and multi-cloud environments.
Drive data discovery initiatives to identify and inventory sensitive data across databases, SaaS applications, endpoints, and cloud storage.
Define and implement data classification frameworks, labeling standards, and data handling policies integrated with DLP and DSPM controls.
Build and maintain DLP detection rules, regular expressions, fingerprinting, and machine learning-based classifiers to minimize false positives and maximize coverage.
Integrate DSPM findings into DLP enforcement workflows to create a closed-loop data protection architecture.
Define and enforce data access governance, including least-privilege principles and monitoring of sensitive data access patterns.
Monitor, triage, and investigate DLP alerts and DSPM-identified risks, collaborating with SOC and Security teams on escalation and remediation.
Conduct risk assessments and identify gaps in data protection controls across systems, pipelines, and business processes.
Support compliance and regulatory requirements (e.g., GDPR, ISO 27001, SOC 2) related to data security and privacy.
Collaborate with Engineering, IT, Product, and GRC teams to embed data security controls into CI/CD pipelines, systems, and workflows.
Maintain documentation, runbooks, and guidelines for DLP operations, DSPM posture management, and data security practices.