דרושים » אבטחת מידע וסייבר » Security Researcher - R&D

We're looking for a Threat Security Researcher to join our Threats team at the intersection of security research, AI, and product. You'll own detection research across runtime, cloud, network, identity, code, while actively shaping how AI capabilities are applied to solve real security problems at scale.
Conduct deep technical research into modern cloud environments and AI systems and discover novel attack techniques.
Lead product initiatives in the threats domain from inception to production. Collaborate closely with product, backend, and GTM, translating research into product capabilities.
Define and create complex detection logic over our vast telemetry, with a focus on coverage that scales across customer environments.
Identify gaps in detection coverage and evaluate detection quality. ensuring security logic is reliable and impactful.
Stay up to date with the evolving threat landscape (threat intelligence, campaigns) and incorporate into our product
Contribute to PR presence - technical research content, talks, open-source tooling.

About GeoEdge GeoEdge is the global leader in ad security, trusted by hundreds of the world's top ad platforms, publishers, and app developers. Our mission: make the internet safer by stopping malicious, deceptive, and low-quality ads before they ever reach a user. For over a decade, we've protected the integrity of the digital advertising ecosystem with real-time technology that empowers our partners to deliver clean, trustworthy user experiences. The Role Malvertising attackers are already using AI to hide their campaigns. We're building the detection technology that beats them, and we need a leader who can make it the best in the world. As our Head of Security & Research, you'll report directly to the CEO and own GeoEdge's malvertising detection vision, combining deep security research with AI and agentic innovation. You'll lead our security research team, uncover new attack techniques before they reach users, and turn that insight into detection that works in real time at massive scale. You'll build a research agenda that puts GeoEdge on the stage at the world's top security conferences, and partner with Product, R&D, Data Science, Customer Support, and other key functions inside and outside the company to bring it to market. You'll be the security and research voice of GeoEdge for customers, partners, and the wider security community. What You'll Do Set the strategy and roadmap for GeoEdge's malvertising detection and security research Lead, mentor, and grow the security research team Drive AI and agentic innovation in detection, working with R&D and Data Science to turn research into production-grade capabilities Uncover and track emerging malvertising threats, evasion techniques, and attacker campaigns across the ad ecosystem Own detection quality: push for uncompromising precision, coverage, and speed Drive original research and publications, and represent GeoEdge at leading security conferences Partner with Product, R&D, Data Science, Customer Support, and other key functions in the organization and outside of it Report to the CEO and management on research impact, threat landscape, and priorities

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.

As a Security Researcher , you will play a key role in shaping the future of modern runtime and AI security. You will investigate how real-world attacks unfold across applications and cloud environments, and turn those insights into innovative, production-grade security capabilities.

This role is ideal for a deeply technical researcher who is driven to understand attacks at their core - not just identify surface-level indicators. You will research exploitation chains, runtime behavior, attacker techniques, and emerging AI attack patterns, then apply that knowledge to build protections that are precise, resilient, scalable, and grounded in how attacks actually work.

Specifically, you will:

Research real-world attack techniques targeting modern applications, cloud-native environments, and AI-driven systems.
Design, develop, validate, and deploy detection algorithms based on technical research, large-scale runtime telemetry, threat intelligence, and exploit PoCs.
Shape the strategy for detection data collection by defining the required telemetry, collection points, and data quality standards needed to support effective protection.
Drive research efforts end-to-end, from initial exploration and technical investigation to production-grade protection capabilities for active threats.
Work closely with engineering and product teams to turn research into practical security capabilities.

were the company.
were building the future of product security. our mission is to enable both humans and ai to build secure-by-design software, at scale, without slowing innovation.
were backed by $36m from team8, notable capital, and svci, and trusted by multiple fortune 500 companies.
but funding and logos dont define us. people do.
our about us page offers a real look at our culture, our values, and the people behind the product.
this is where you come in.
were looking for a security researcher to join our research team and drive cybersecurity research at the intersection of product security and ai. you'll investigate security risks in modern software development, including ai-assisted and agentic workflows, and translate research into product capabilities, customer guidance, and industry insights.
what youll do
conduct deep technical research across codebases, architectures, integrations, data flows, permissions, and agentic workflows to identify product security risks that traditional scanners often miss.
investigate how ai coding agents, llm-based workflows, and ai-assisted engineering practices change the way security risks are introduced, missed, prioritized, and remediated.
turn research into useful outputs, including product recommendations, customer-facing guidance, technical writeups, evaluation ideas, talks, and internal briefs.
maintain and evolve the company's threat-pattern corpus, security context modules, and research-backed detection logic.
work with product and engineering to translate findings into shipped capabilities, evals, onboarding materials, and go-to-market narratives.
what were looking for
strong application or product security expertise, with the ability to reason across code, architecture, product behavior, and business context.
a track record of owning research end-to-end: defining questions, doing deep technical work, forming a point of view, and producing useful artifacts.
strong threat modeling judgment, with experience using frameworks such as owasp, stride, or similar methodologies to identify and assess common appsec risks.
heavy hands-on use of ai coding agents, llm-based development workflows, or ai-assisted software engineering tools in real-world engineering/research environments.
strong communication skills, curiosity, independence, and the ability to turn research into outcomes that influence product, engineering, customers, or the market.
if this role excites you - even if you dont check every box - wed love to hear from you.

We're looking for a security researcher with 5+ years of experience to discover new ways vendors put their customers at risk. You'll own research end to end, from the first hypothesis to a shipped capability, and help decide where we looks next.
What You'll Do:
Discover new ways attackers can use vendors to get in, and prove or kill each idea with real data.
Decide which security tools and data sources we should integrate next, and why.
Shape the logic and knowledge behind our AI risk agents.
Build your own tools when the one you need doesn't exist.
Partner with engineering to turn validated research into product.
Work alongside the best security researchers in the industry.

We are looking for a hands-on security researcher who combines an attacker mindset, fraud-domain curiosity, strong technical depth, and data analysis skills. You will investigate real-world fraud patterns, reproduce attacker techniques, analyze telemetry, enrich our data collection capabilities, discover new security signals, and work closely with product, data, and engineering teams to turn research insights into production-grade detection and prevention mechanisms.

This role is especially relevant for researchers with experience in browser technologies, mobile-native applications, or both. You may work on desktop and mobile browsers, browser APIs, browser automation, client-side signals, native mobile applications, Android/iOS behavior, mobile security, emulators, device signals, and mobile automation.

You will help expand our visibility into new signals and patterns that improve fraud detection, model performance, and customer protection.

If you are a talented researcher who enjoys solving complex problems, working with messy real-world data, and building practical defenses against modern fraud and abuse, we want you to join our team.



What youll do:

Research emerging fraud and abuse techniques across account takeover, bots, automation, phishing, social engineering, device spoofing, emulators, remote access tools, suspicious network infrastructure, and related attack vectors.
Identify, design, and validate new data collection opportunities, security signals, behavioral patterns, device indicators, browser indicators, and mobile app indicators.
Analyze real-world telemetry, customer-provided labels, behavioral signals, device signals, network indicators, and attack patterns to identify detection opportunities.
Reproduce attacker techniques in lab and production-like environments, generate telemetry, identify detection gaps, and translate findings into detection logic.
Design, validate, and tune detection and prevention mechanisms with attention to coverage, explainability, false positives, customer impact, and production stability.
Build research infrastructure, analysis workflows, and internal tools using Python.
Produce robust data features that can later be used by machine learning models, detection logic, rules, dashboards, and customer-facing insights.
Work with model training pipelines, evaluate model behavior, compare training and validation results, and help determine whether new features improve detection quality.
Collaborate closely with data science, engineering and product, teams to take ideas from research hypothesis through validation, implementation, monitoring, and production feedback.
Stay up to date with fraud trends, attacker tooling, automation frameworks, browser abuse techniques, mobile abuse techniques, malware behavior, phishing techniques, and underground ecosystem developments.
Communicate findings clearly to technical and non-technical stakeholders, including recommended actions, tradeoffs, expected impact, and model/detection quality considerations.

The Exposure Management Research Group at our company Software Technologies is expanding. We are looking for an experienced Offensive Security Researcher to join our newly formed AEV Team and lead the offensive side of our Agentic Exposure Validation (AEV) research.
About the group
The Exposure Management Research Group is the research arm behind our company's Exposure Management platform. The platform helps organizations see and reduce their risk from the outside in, across their external attack surface, threat intelligence, and digital risk. The group brings together vulnerability researchers, threat intelligence analysts, phishing researchers, and data scientists. Together, we track threat actors and campaigns, analyze vulnerabilities and active exploitation, and turn that research into detections, intelligence, and validation capabilities that serve thousands of customers worldwide. Our work relies heavily on data science, machine learning, and agentic AI to operate at scale.
About the position
Exposure validation goes beyond identifying that a vulnerability exists. Its purpose is to show whether an attacker could actually exploit that vulnerability, and how far they could get. In this position, you are responsible for bringing real offensive expertise into our AEV capability, which runs on an agentic AI system that validates exposures across our customers' environments.
You conduct hands-on offensive research, define the exploitation methodologies the system follows, and set the standard for what a validated, customer-ready finding looks like. You also work closely with our threat intelligence and detection teams, so that proven attack paths turn into protections for our customers.
This is a research position with direct product impact. It combines practical red team work with shaping how an AI-driven platform conducts, reasons about, and reports offensive activity.
What you'll do
Design and run offensive research against external attack surfaces: web applications, APIs, cloud-exposed services, identity, and edge infrastructure
Turn single findings into demonstrated impact through exploit chaining, lateral movement, and blast-radius analysis
Write and maintain the exploitation methodologies and attack hypotheses our agentic AEV engine runs on
Review agent runs and findings. Separate proven impact from claimed impact, and turn the gaps you find into better prompts, methods, and guardrails
Set the bar for customer-ready findings: a clear impact story, a reproducible chain, and remediation guidance a security team can act on
Work with threat intelligence researchers to turn in-the-wild attacker behavior (named actors, active campaigns, newly exploited vulnerabilities) into validation plays
Help close the purple loop by turning proven attack paths into detection and protection logic, and working with detection engineering on coverage
Contribute to the team's research output, including internal knowledge sharing and, where it fits, external publications and talks.

We're looking for a Cloud Security Researcher to join the platform research team. This is a chance to shape the platform end to end- expand what it sees, define how it thinks about risk, and build the AI systems that act on what it finds
What You'll Do:
Integrate new systems and domains- from cloud to shift-left tooling and AI providers- model their data, analyze and enrich it with context from across the platform to generate meaningful insights
Map risk vectors, build threat models, and translate them into actionable posture recommendations
Define how the platform should reason about risk, advancing posture management beyond static rules toward dynamic approaches like graph traversal and reachability analysis
Shape how AI is applied on top of the platform's findings - from agentic systems for insight, context analysis, and remediation to smarter prioritization and prevention
Lead research initiatives end-to-end, working with product and engineering to turn them into shipped capabilities