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description
we are a global leader in control systems for quantum computing, a field on the verge of exponential growth. our innovative hardware and software mark a groundbreaking approach in quantum computer control, scaling from individual qubits to expansive arrays of thousands. at the core of our company lies a passionate and ambitious team committed to reshaping the construction and operation of quantum computers. our work is fueled by a deep understanding of customer needs, driving us to deliver unparalleled solutions in this revolutionary field.
we are seeking a highly experienced microsoft 365 cloud security engineer to own the administration, configuration, and security of our enterprise microsoft 365 tenant(s). the ideal candidate has proven hands-on expertise managing microsoft 365 at scale, including intune, exchange online, SharePoint /onedrive, teams, entra id, defender, and related integrations
you will play a key role in ensuring availability, governance, identity and access control, endpoint compliance, and modern security posture across the entire microsoft cloud ecosystem, with close collaboration across it, security, and business stakeholders.
key responsibilities
microsoft 365 tenant administration
administer and maintain enterprise-scale m365 tenants, including configuration, governance, and operational support.
oversee service health, usage reporting, licensing, and user lifecycle management.
maintain documentation of configurations, workflows, and operational procedures.
microsoft intune / endpoint management (full scope)
own all aspects of intune administration, including:
device enrolment (windows, macos, IOS /ipados, Android )
configuration profiles, compliance policies, and security baselines
autopilot provisioning, device naming policies, and lifecycle
conditional access integration with device compliance
endpoint security policies (av, firewall, asr rules, bitlocker, etc.)
identity & access management (entra id / sso)
manage and secure microsoft entra id (azure ad) for identity, authentication, and access governance.
configure and maintain sso integrations with saas applications using saml/oauth/oidc.
implement and optimize:
conditional access policies
mfa enforcement and authentication methods policy
privileged identity management
identity protection policies (risk-based controls)
security & threat protection
deploy and manage microsoft defender stack relevant to the organization
integrate and manage endpoint security posture with non-microsoft edr platforms, such as sentinel one/crowdstrike
collaborate with security teams to implement detection and response workflows, ensure coverage, and align with organizational policy.
messaging & collaboration
exchange online
administer exchange online policies and configurations
implement email security best practices and support incident response when needed.
microsoft teams
administer teams policies and governance - teams lifecycle policy, app permissions, meeting policies; external access and guest collaboration settings
SharePoint / onedrive
administer SharePoint online and onedrive settings, including:
site governance, permissions, and sharing controls
sensitivity labels and information protection controls (if used)
sync and Storage management, auditing and access policies
azure & cloud infrastructure
support azure identity, security, and basic cloud resources relevant to m365 integrations.
manage azure configuration related to:
entra id integrations
conditional access
hybrid identity (if applicable)
azure security settings and monitoring
policy, compliance, and governance
implement and maintain governance models across identity, endpoint, data sharing, and collaboration tools.
support compliance initiatives, audits, and reporting needs.
maintain secure tenant configurations aligned with best-practice frameworks (e.g., cis, microsoft secure score, nist).#ENGLISH המשרה מיועדת לנשים ולגברים כאחד.

As a Principal/Senior Applied Scientist, you will own end‑to‑end model development for security scenarios, including developing new model architectures, continual pre‑training, task‑focused fine‑tuning, reinforcement learning, and objective, benchmark‑driven evaluation.
You will drive training efficiency and reliability on distributed GPU systems, deepen model reasoning and tool‑use capabilities, and embed Responsible AI, privacy, and compliance into every stage of the workflow. The role is hands‑on and impact‑focused, partnering closely with engineering and product to translate innovations into shipped, measurable outcomes, defining quality gates and readiness criteria, and mentoring scientists and engineers to scale results across globally distributed teams.
You will combine strong coding, experimentation, and debugging skills with a systems mindset to accelerate iteration cycles, improve throughput and cost‑effectiveness, and help shape the next generation of secure, trustworthy AI for our customers.
Responsibilities:
Youll work as part of an Applied Science team on high-impact, technically ambitious AI projects that directly shape the future of AI in Cyber security, with ownership for taking advanced research through to production impact.
Technical Leadership & Ownership: set technical direction for major security domain initiatives; lead security model programs spanning pre‑training, task tuning, reinforcement learning, and evaluation; translate cutting‑edge research into production‑ready capabilities.
Advanced Model Design - Building and customizing deep learning model architectures (e.g., modifying transformer blocks, attention/memory modules, etc.) at the SLM/LLM scale; making principled architectural tradeoffs to improve reliability, robustness, and security‑specific behavior.
Advanced Model Training - Apply deep expertise in pre-training, post-training, and reinforcement learning (RL) for both language and other modalities, including time-series.
Design & Evaluate Datasets - Build high-quality datasets and benchmarks; define objective evaluation frameworks and quality gates; run ablation studies to measure impact and optimize data and training effectiveness to support confident product decisions.
Develop Data Infrastructure - Create and maintain scalable pipelines for ingestion, preprocessing, filtering, and annotation of large, complex datasets, with attention to privacy, governance, and long‑term reuse across security scenarios.
Research & Innovation - Collaborate with cross-functional teams to push research and product boundaries, delivering models that make a real-world impact.