דרושים » אבטחת מידע וסייבר » Cloud Security Engineer - Microsoft 365

we are seeking a highly qualified Security Expert with demonstrated experience in Azure services, Microsoft Sentinel, Anthropic for enterprise, enterprise AI, as well as Agentic and autonomous AI technologies. In this role you will secure modern cloud and AI platforms across the enterprise, partnering with architecture, IT, and business teams to assess risk, define controls, and enable safe adoption of emerging technologies.
??מה תעשו בתפקיד? ניסיון של 5+ שנים בעולמות אבטחת מידע וסייבר בסביבת Microsoft שליטה מעשית ב Microsoft Defender, Sentinel וE5 Security ניסיון בעבודה עם פתרונות: Endpoint | Identity | Cloud Apps ידע מעמיק ב Entra ID כולל:? Conditional Access? MFA? RBAC? PIM? PURVIEW ניסיון Hands-On בעולמות הסייבר בענן ובסביבות Microsoft ניסיון בעבודה מול צוותים מרובי ממשקים בארגונים גדולים שליטה ב PowerShell (כתיבת סקריפטים) ניסיון בכתיבת מסמכי אפיון טכניים?? הסמכות Microsoft - יתרון?? סיווג ביטחוני - יתרון?? אנגלית ברמה גבוהה

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.

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.

Required Security Operations & Automation
About Your Day-to-Day:
As a Security Operations & Automation, you'll be the hands-on architect of how we detect, investigates, and responds to threats - built around AI agents and deep tooling integrations, not manual triage. You'll own incident response across corporate systems, workstations, and identity, unify alerts from every source - including cloud-originated signals that need a response - into a single SOAR/XDR fabric, and deploy AI agents to handle first-line investigation and response.
You'll work closely with IT and the Cloud Security team - taking the lead on investigation, triage, and response while they own the underlying cloud and SDLC architecture - and turn complex security signals into structured, AI-assisted, largely autonomous outcomes - fighting fire with fire.
Responsibilities:
Architect and own our AI-driven detection and response stack, integrating SIEM, XDR, SOAR, EDR, and IAM into a single automated fabric rather than siloed tools.
Deploy and tune AI agents to handle first-line alert triage, enrichment, and investigation, with humans engaged only for true edge cases - manual L1 triage is the exception, not the default.
Build SOAR playbooks and integrations across the security and IT toolchain (endpoint, identity, ticketing, chat) so detection, enrichment, and remediation run automatically end to end - regardless of which system or platform an alert originates from.
Own the alert pipeline as a whole: unify signals from EDR, IAM, and other sources - including cloud and SaaS alerts surfaced by the Cloud Security team - into one triage and response workflow, so nothing falls through the cracks between tools.
Evaluate and integrate best-of-breed, AI-native security tools - SIEM, XDR, SOAR, EDR, email security, AI guardrails, ZTNA, and others - wiring each into the unified detection and response fabric rather than running them as siloed point solutions. Hands-on tool integration (APIs, connectors, log and telemetry ingestion) is a core skill for this role, not an occasional task.
Drive vulnerability and patch management across corporate systems and endpoints, automating prioritization and remediation workflows and coordinating with IT against strict SLAs.
Build and tune detection rules specific to our environment, treating detection as code and feeding AI-driven correlation across the XDR layer.
Maintain security dashboards (MTTD/MTTR, automation rate, % of alerts resolved without human touch) and report on how automation is cutting noise and response time.