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Were looking for a Field Security Architect to serve as a trusted advisor to our customers, helping them adopt our company and build secure-by-design practices across their SDLC.
This role sits at the intersection of Application Security, Customer Success and Advisory, and Product, with a clear focus on driving measurable customer value and security outcomes.
What youll do
Own the post-sale journey (onboarding → adoption → maturity) and drive retention & expansion
Act as a trusted advisor on secure design, threat modeling, and SDLC integration
Lead adoption of our company and translate security needs into actionable workflows
Deliver onboarding, workshops, and architecture/design sessions
Partner with Product, R&D, and Sales to drive customer impact and feedback
Proactively manage customer risks, challenges, and escalations
Drive measurable security outcomes and help customers mature their security programs.

We are looking for a visionary engineering leader to architect and lead our quality engineering discipline into the AI era. You will own automation infrastructure, performance engineering, and all AI-driven quality initiatives - building and mentoring high-performing teams of engineers and architects who set the standard for how modern software is validated at scale.
This is not a maintenance role. You will disrupt legacy testing paradigms, champion agentic test generation, and embed AI-quality thinking into every stage of the SDLC - from the first commit to production monitoring. You will be the organizational bridge between engineering velocity and product reliability.
How will you make an impact?
AI Quality Strategy:
Define and lead all AI-augmented quality initiatives across the organization
Deploy LLM-powered test generation, triage, and root-cause analysis tooling
Build frameworks for validating AI/ML model outputs and non-deterministic behaviors
Evaluate and integrate emerging AI quality toolchains (GitHub Copilot, Claude, agents)
Champion responsible AI testing practices, coverage standards, and governance models
Automation Engineering:
Own the full automation strategy across UI, API, and integration layers
Architect scalable, maintainable test frameworks
Drive shift-left testing embedded in CI/CD pipelines (Jenkins, GitHub Actions)
Establish coverage KPIs, flakiness SLAs, and automation ROI metrics
Lead adoption of self-healing and AI-assisted test maintenance
Performance Engineering:
Lead performance and load testing strategy at enterprise scale
Define SLOs/SLAs and partner with SRE on reliability thresholds
Design continuous performance validation integrated into delivery pipelines
Drive root-cause analysis for regressions, bottlenecks, and latency spikes
Oversee toolchain including k6, JMeter, Gatling, and APM integrations
People & Org Leadership:
Lead and grow teams of automation engineers, performance engineers, and architects
Set technical direction, OKRs, and career ladders for the quality engineering org
Hire senior ICs and architect-level talent; build succession depth
Foster a culture of ownership, engineering craft, and continuous learning
Partner cross-functionally with Product, DevOps, and R&D leadership.

We are looking for a Platform Security Director to lead the engineering of our security infrastructure. Your mission is to build a Security Machine that is as sophisticated as our AI. You will move us beyond traditional "defense" into a "Secure-by-Default" reality, where our multi-cloud infrastructure (AWS and Azure) is hardened, automated, and resilient by design.
Youll Own:
The end-to-end security strategy across Application Security, Cloud (AWS/Azure), and Platform layers, ensuring a Secure-by-Default framework, as measured by deployment coverage, critical vulnerability reduction, and developer adoption metrics.
A unified Security Engineering organization covering AppSec, SecDevOps, and AI Security leadership, collaboration points with adjacent teams (Infrastructure, R&D, Product Engineering), and building and mentoring a high-performing team.
Lead our Platform Security domain - from Layer 7 protections to AWS architecture, security tooling, automated risk scoring, and AI-assisted automation workflows that improve detection and remediation times.
Security controls (WAF, Rate Limiting) embedded into the SDLC and CI/CD pipelines, including mandatory security gates, artifact scanning, and automated deployment checks.
Lead our AI strategy - enabling secure use in our platform products as well as for our internal engineering usage, and scaling AI security governance and controls.
The evolution of scalable infrastructure security, including Kubernetes, containers, IAM, and Zero Trust architectures, strengthening Kubernetes and cloud security posture.
Own and execute the comprehensive Vulnerability Management program, from discovery (SAST/DAST/OSS scanning) through remediation tracking, and manage the external Bug Bounty program, with a focus on improving remediation SLAs and automation coverage.
Mature secure-by-default engineering practices across the SDLC.
Increase developer adoption of automated security tooling.
Youll Solve:
Eliminating manual bottlenecks through code-driven guardrails and frictionless developer experiences.
Securing complex production systems and multi-tenant AI architectures in cloud-native production environments, with a focus on model integrity, training data provenance, data exfiltration prevention, and minimizing unique risks associated with Large Language Models (LLMs), by applying specific AI threat models.
Operationalizing Red/Purple Team exercises, penetration testing, and the Bug Bounty program to ensure a continuous feedback loop that drives proactive risk reduction.
Youll Impact:
Support a culture where security is embedded into the foundation of engineering
Turn security into a strategic product advantage and customer trust differentiator
Improve developer experience by making the secure path the easiest path
Increase engineering velocity while strengthening platform resilience
Shape the future intersection of Security, AI, and Platform Engineering
Create scalable systems, processes, and relationships that grow with the companys innovation pace.

We're looking for a talented AI Security Researcher to join our team and play a critical role in our foundational, risk-driven approach to cloud security. This role requires deep technical research into complex cloud- and AI-native environments to identify the most significant, unaddressed risks.
Responsibilities
Conduct deep technical research to discover and report novel risks and attack vectors specific to modern cloud- and AI-native architectures and systems.
Discover and articulate the highest unaddressed risk areas, working with Product and Engineering teams to translate research into product capabilities.
Define necessary foundational product capabilities by delivering both compelling proofs of risk (demonstrating impact) and technical POCs (showing how to solve it).
Work closely with Product and Engineering teams to ensure comprehensive risk coverage and support the investigation of new and complex product scope.

As a Principal/Senior Windows Exploit Researcher, you will be a key member of our Tel Aviv R&D center, responsible for leading research into Windows Anti-Exploit capabilities. You will leverage your top-notch knowledge of the latest exploitation techniques and deep Windows internals to architect and develop the next generation of security protections. Your work will directly contribute to safeguarding our customers from the most sophisticated cyber threats.
Key Responsibilities
Lead advanced research into novel vulnerabilities and complex exploits targeting the Windows operating system.
Architect, develop, and improve sophisticated anti-exploitation mitigations using low-level OS mechanisms, challenging the status quo with innovative solutions.
Drive the design, evaluation, and implementation of next-generation security technologies from conception to deployment.
Develop proof-of-concept (POC) exploits to validate research findings and test the effectiveness of new and existing mitigations.
Analyze customer escalations to help with detecting and preventing malicious activities in our customers networks
Publish research done internally.

we are seeking an experienced Manual QA Engineer - Digital & Web Systems to perform comprehensive manual testing across digital, Web, and operational systems. In this role, you will perform End-to-End testing, API testing, database validation, TEST documentation, and defect management while working closely with development, QA, and business teams. This is a full-time position located in central Israel. Key Responsibilities: Perform comprehensive manual testing across digital, Web, mobile, and operational systems. Write and execute detailed TEST scenarios ( STD ) and document defects. Perform API and integration testing using Postman or similar tools. Work with databases and write SQL queries for data validation and testing. Perform End-to-End (E2E) testing across complex systems and interfaces. Analyze system flows and validate integrations between Front-End, back-end, and enterprise systems. Manage and track defects using tools such as Azure DevOps, Jira, or Monday. Work closely with Developers, QA Management, Team Leaders, and business stakeholders in an Agile environment.

We are looking for a visionary engineering leader to architect and lead our quality engineering discipline into the AI era. You will own automation infrastructure, performance engineering, and all AI-driven quality initiatives - building and mentoring high-performing teams of engineers and architects who set the standard for how modern software is validated at scale.
This is not a maintenance role. You will disrupt legacy testing paradigms, champion agentic test generation, and embed AI-quality thinking into every stage of the SDLC - from the first commit to production monitoring. You will be the organizational bridge between engineering velocity and product reliability.
How will you make an impact?
AI Quality Strategy:
Define and lead all AI-augmented quality initiatives across the organization
Deploy LLM-powered test generation, triage, and root-cause analysis tooling
Build frameworks for validating AI/ML model outputs and non-deterministic behaviors
Evaluate and integrate emerging AI quality toolchains (GitHub Copilot, Claude, agents)
Champion responsible AI testing practices, coverage standards, and governance models
Automation Engineering:
Own the full automation strategy across UI, API, and integration layers
Architect scalable, maintainable test frameworks
Drive shift-left testing embedded in CI/CD pipelines (Jenkins, GitHub Actions)
Establish coverage KPIs, flakiness SLAs, and automation ROI metrics
Lead adoption of self-healing and AI-assisted test maintenance
Performance Engineering:
Lead performance and load testing strategy at enterprise scale
Define SLOs/SLAs and partner with SRE on reliability thresholds
Design continuous performance validation integrated into delivery pipelines
Drive root-cause analysis for regressions, bottlenecks, and latency spikes
Oversee toolchain including k6, JMeter, Gatling, and APM integrations
People & Org Leadership:
Lead and grow teams of automation engineers, performance engineers, and architects
Set technical direction, OKRs, and career ladders for the quality engineering org
Hire senior ICs and architect-level talent; build succession depth
Foster a culture of ownership, engineering craft, and continuous learning
Partner cross-functionally with Product, DevOps, and R&D leadership.