Our Identity Protection Product Group in Israel has grown into one of the highest-performing teams, driving significant ARR growth while tackling one of cybersecurity's hardest problems: identity posture at cloud scale. As a Senior Engineer on the Entities team, you'll own the full entity lifecycle - from scraping identity data across Active Directory, Azure, and cloud providers, through enrichment and risk scoring, to publishing millions of identity entities into our asset platform. Your systems are the foundation that detection rules, alert pipelines, and customer-facing dashboards all depend on. You'll tackle real-world scale challenges: processing massive volumes of identity data through complex dependency graphs, maintaining data consistency across distributed regions, and building new high-performance Go microservices to replace and extend legacy systems.

What You'll Do:

Own the entity enrichment pipeline - a DAG-based computation engine that calculates 100+ fields, risk scores, and privilege relationships for every identity entity.

Build and maintain data ingestion services that scrape Active Directory forests, process cloud assets from Azure/AWS via Kafka, and integrate third-party identity sources.

Design and develop new Go microservices as the team migrates performance-critical paths from Node.js/Java to Go.

Solve complex data pipeline challenges: dependency ordering, incremental computation, race condition handling, and cache invalidation at scale.

Publish entity data to our centralized asset graph (SDMF), ensuring correctness and freshness for millions of identities - Optimize system performance - reduce enrichment latency, improve throughput, and handle traffic spikes gracefully - Mentor and elevate engineering talent, sharing expertise in building production systems that work under pressure.

The Falcon Secure Access (FSA) team is expanding. As a Senior Software Engineer on our team, you will architect and deliver a next-generation secure access platform that converges Zero Trust Network Access with browser-native security.

You'll build the core systems that enable users to seamlessly and securely access internal sites, private applications, and cloud resources directly from the browser - without legacy VPNs or remote desktops - while enforcing real-time protection against zero-day exploits, phishing, data exfiltration, and unauthorized access.

This role sits at the intersection of network engineering and browser security: you'll design and implement advanced proxy communication, secure tunneling, and identity-aware routing - all operating at the browser's core to deliver holistic protection including DLP, insider threat detection, SaaS security, and continuous zero-trust verification.

What You'll Do:

Design and build ZTNA infrastructure - implement zero-trust access policies, secure tunneling, and identity-aware network routing that replaces traditional VPN architectures.

Develop advanced networking solutions - build and optimize proxy communication layers, WebSocket-based transport, and encrypted client-to-server channels that handle millions of concurrent connections.

Architect high-scale backend systems - design distributed microservices for policy enforcement, real-time threat detection, and access control at scale using Node.js / TypeScript.

Implement secure client-server communication - design highly secured agent-to-cloud architectures with certificate pinning, mutual TLS, and encrypted tunneling protocols.

Build browser-native security components - develop browser extensions and agents (Chrome, Edge, Firefox etc.) that enforce data protection, prevent data leakage, and provide granular visibility and control.

Own features end-to-end - from design through delivery, including deployment and monitoring.

Influence architecture and roadmap - play a key role in architectural decisions, building toward an efficient distributed zero-trust architecture.

Research and develop - drive new initiatives and POCs in zero-trust access domains and browser security.

Collaborate cross-functionally - work with security researchers, product, and platform teams across multiple locations to solve complex problems.

We're looking for a Threat Detection Researcher to join the Threat Research team and spread the power. In this role, you will further develop the Cloud-native Threat Detection domain.
Check out some of our recent research:
Detecting Malicious OAuth Applications
Tracking TeamPCP: Investigating Post-Compromise Attacks Seen in the Wild
Discovers Cloud Email Abuse Campaign
Responsibilities
Drive the full lifecycle of security detections - from threat research and data analysis to building and shipping detection logic directly into production.
Design behavioral baselines for complex cloud environments using diverse signals, and develop high-fidelity detections based on those baselines.
Expand our detection engine with novel and high-impact telemetry sources, pushing the boundaries of what can be detected in modern cloud environments.
Conduct deep technical research into complex cloud services to uncover novel attack vectors.
Investigate real-world attacks across cloud environments, identity providers (IDPs), and infrastructure-as-a-service (IaaS) platforms.
Hunt and analyze emerging threats and active campaigns targeting the cloud ecosystem.

We are seeking a Software Engineer to join Dashs core development team. You will design, build, and ship the platform that powers discovery, session-aware detection, policy governance, and runtime enforcement across workstations, SaaS, and cloud. You will work on scalable, low-latency services that process agent activity in real time and enforce security policies without slowing builders down. This role requires strong engineering fundamentals, a focus on system reliability, and an interest in the unique challenges of agentic security.
Responsibilities:
Design and Implement Services: Design, develop, and deploy scalable backend services and APIs for the Dash Security platform (customer and admin APIs, detection ingestion, aggregation, and control-plane services).
Build Core Features: Implement features for agent/MCP/skill discovery, session and intent-aware detection, policies, and runtime enforcement across coding agents and enterprise AI platforms.
Optimize Runtime Protection: Maintain and optimize high-throughput detection and enforcement pipelines that operate at enterprise scale (ingestion, detectors, verdicts, and policy dispatch).
Integrate with Platforms: Build and deepen integrations with coding agents, SaaS AI platforms, identity providers, EDR, SIEM, and outbound action systems to ingest telemetry and enforce controls.
Ensure Reliability: Focus on code quality, performance, monitoring, and stability through robust testing, CI/CD, and operational excellence.
Collaborate with Research: Partner with the AI Security Research team to turn findings, signatures, and heuristics into production-ready detectors and enforcement logic.
Contribute to Architecture: Participate in technical design and architectural reviews across our codebases, agents, and event-driven backend services.
Stay Current: Continuously learn and apply new technologies, development methodologies, and security best practices.

we are looking for a Lead Detection Engineer.This is an individual contributor role with full technical ownership. You'll set the direction for detection engineering: the standards, the tooling, the coverage strategy, and the automation that operationalizes it all. You'll work closely with SOC analysts and Platform Engineering to make detection a first-class engineering discipline.

Youre welcome to work in our offices in Tel Aviv, Israel

Your responsibilities will include:

Detection coverage strategy across endpoint, identity, cloud, and infrastructure - how it's measured, prioritized, and continuously improved.
Detection-as-Code pipeline: version control, testing, peer review, CI/CD, and deployment practices for all detection logic.
Architecture connecting detections to enrichment, triage, and automated response workflows.
Technical standards for how detections are designed, tested, documented, deployed, and retired.
Detection quality: fidelity metrics, false positive reduction, coverage measurement, and continuous validation loops.
Design and build high-fidelity behavioral detections across SIEM and EDR platforms.
Research emerging attacker techniques and translate threat intelligence into scalable, evasion-resistant detections.
Validate detections through threat simulations and continuous detection testing.
Partner with SOC analysts to close the feedback loop between detections and real investigations.
Define and track detection engineering metrics; communicate coverage posture and effectiveness to security leadership.
Make architectural decisions that scale as the team and organization grow.

Were looking for driven and talented people like you to join our R&D team and our mission to change the future of cloud security.

As a Senior Software Engineer on the KSPM team, you will join a mission-critical group building and scaling one of the companys core and fastest-growing security products. Our team enables customers to secure their Kubernetes environments across every major cloud provider, delivering deep visibility into cluster misconfigs, RBAC risk, admission control, compliance drift and container vulnerabilities.

In this role you will design the backend services and data models that discover, onboard, scan, and represent K8s workloads, APIs, and configurations at scale. You will own core services end-to-end, drive architectural improvements and partner with security researchers to turn complex threat vectors into actionable insights.

We are looking for backend engineers who care deeply about software design, cloud-native infrastructure, and container security. This is a high-impact role with real ownership - lead features end-to-end, mentor teammates, and help shape the technical direction of our KSPM offering.

What Youll Do:
Design & build at scale: Design, implement, and maintain scalable backend services that discover, onboard, scan, and analyze Kubernetes environments across multi-cloud and managed clusters.
Model K8s security: Map and represent Kubernetes resources as clean data models that surface misconfigurations, exposure risks, and compliance violations.
Integrate detection engines: Integrate and evolve detection engines for container vulnerabilities, secrets, RBAC risks, misconfigurations, and compliance frameworks.
Collaborate on research & product: Partner with security researchers and product managers to translate novel findings and complex requirements into impactful features.
Design for quality: Write clean, well-tested code in Python or Go, with thoughtful abstractions and APIs that keep the system correct and maintainable as it grows.
Lead & mentor: Lead design discussions and code reviews that uphold high engineering and security standards across the team.
Own it end-to-end: Own features through their full lifecycle - from technical specification and design through implementation, testing, and release.

we are looking for a SecOps Detection & Response.
As a Security Operations Analyst, Detection & Response, you will help protect Aidocs cloud environments, products, corporate systems, and sensitive healthcare data by investigating SIEM alerts, supporting incident response, and improving the quality of security monitoring.

This is a hands-on security operations role for someone who can analyze security signals, understand real risk, communicate clearly, and help the organization respond quickly and effectively to security events.

You will work closely with real production environments, where accurate investigation, clear documentation, and practical escalation are critical to protecting sensitive healthcare data, customer trust, and the reliability of clinical AI platform.
Responsibilities:
Own the end-to-end investigation of SIEM alerts across cloud, product, identity, endpoint, and SaaS environments: analyze the relevant evidence, separate false positives from real threats, and prioritize cases based on risk and impact.
Escalate high-risk findings with a clear summary of what happened, what is affected, why it matters, and what actions are required.
Support incident response by collecting evidence, assisting with containment, tracking remediation, and maintaining clear investigation records for internal reviews, compliance needs, and post-incident learning.
Improve SIEM rules, dashboards, alert logic, playbooks, telemetry coverage, and detection quality to reduce noise and strengthen security monitoring.
Work with Security, IT, DevOps, R&D, Product Security, and Compliance teams to resolve issues and improve security operations.

Appdome's mission is to protect every mobile app in the world and the people who use them. We are the leader in AI-native mobile business protection, providing cyber and fraud teams with an agentic platform that builds, monitors, and maintains security defenses in Android and iOS apps — with no SDKs, no coding, and no disruption to engineering cycles.
Our platform delivers over 400 security, anti-fraud, anti-bot, and API protection capabilities, powered by deep learning models trained on a decade of mobile defense data and trillions of live threat events. From build time to runtime, Appdome's AI Agents help mobile brands detect, investigate, and respond to threats faster than ever — recognized as the best AI Platform for Cyber Resilience at RSA Conference 2026 for the second consecutive year. Leading financial, healthcare, m-commerce, and B2B brands rely on Appdome to secure over 50,000 mobile apps and protect more than 1 billion end users globally.
Appdome is an Equal Opportunity Employer. We are committed to diversity, equity, and inclusion in our workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law. All qualified applicants will receive consideration for employment without regard to any of these characteristics.
About the Role We are looking for a talented Software Engineer to join Appdome's Identity Group. You will take part in building advanced fraud detection capabilities, working closely with security researchers and data teams to develop cutting-edge solutions that protect hundreds of millions of mobile devices.
Responsibilities
* Design and develop core components of fraud detection systems from early prototyping through production-ready releases.
* Build scalable backend services and distributed systems that process data at scale.
* Work with large-scale datasets and collaborate with data teams to create actionable signals and features.
* Write high-performance, production-quality code in C and C++ optimized for reliability and performance.
* Take ideas from rapid proof-of-concept through to production, tackling complex engineering challenges across the full development lifecycle.

We are seeking an AI Security Researcher to join Dashs core research team. Youll investigate how AI agents - spanning coding agents, SaaS AI platforms, cloud, and endpoints - can be abused, and design detections that stop threats before they cause impact. Each platform is different, yet they share common risk patterns across prompts, tools, MCP servers, skills, hooks, identity, and data movement. Your mission is to master both: uncovering unique attack surfaces while building universal, session- and intent-aware defenses. This role combines deep platform research, responsible security testing, and close collaboration with engineering to translate findings into production runtime protection. You will help define the field of Agentic Security.
Responsibilities:
Research agentic threats: Prompt injection, tool/plugin/MCP abuse, skill and hook misuse, rogue autonomy, identity misuse, data leakage, adversarial AI, and protocol exploitation across coding agents and enterprise AI platforms.
Develop runtime detections: Design detections for multiple environments (coding agents, SaaS AI, cloud, endpoints), leveraging platform hooks, APIs, telemetry, and native guardrails where available.
Analyze platform complexities: Deep-dive into architectures, permissions, workflows, and agent capabilities (MCP servers, Skills, plugins, extensions) while extracting cross-platform risk patterns.
Build scalable detection logic: Prototype and refine heuristics, signatures, and intent-aware detectors that hold up at enterprise scale with low friction for builders.
Investigate monitoring and enforcement boundaries: Push what platforms allow for visibility and control - hooks, plugins, configuration surfaces, inventory signals, and policy enforcement points.
Prototype PoCs: Validate attack paths end to end, then turn findings into production-ready signatures, heuristics, detectors, and runtime policies.
Collaborate with engineering: Embed research into Dashs detection pipelines, session-aware runtime protection, and policy/governance modules.
Stay ahead of the field: Track adversarial AI and agent security research, continuously evolving Dashs detection and enforcement coverage.