דרושים » AI » Lead Endpoint Researcher

We are seeking a Senior / Principal Security Researcher to join our high-caliber Security ML Team. Our team solves complex security challenges using disruptive technologies, AI/ML algorithms, and massive datasets to design and develop groundbreaking security solutions that transition directly from research into production-grade protection.
In this role, you will serve as the core security domain expert within a multidisciplinary team, providing essential security-side expertise to assist in the development of ML models, deeplearning models, and Small Language Models (SLMs). By translating complex malware behaviors and static file attributes into actionable logic, your research will directly shape the algorithms that protect millions of endpoints worldwide. If you are looking to autonomously drive high-impact research initiatives from inception to production and use data-informed critical thinking to influence advanced security modeling, we want to hear from you.
Key Responsibilities
The Bridge to the AI Ecosystem: Serve as the core security domain expert within a multidisciplinary team, translating complex malware behaviors and static file attributes into actionable features, labels, or heuristics-fueling AI algorithms and automated, data-driven security logic.
Telemetry & Sensor Optimization:Analyze raw endpoint telemetry (such as memory buffers, hook outputs, and IPC artifacts) to evaluate algorithm effectiveness and work with AI researchers to tweak or implement new models..
Deconstruct File Behavior: Look past the "black box" of machine learning by digging into executable formats (PE, ELF, Mach-O) and scripts to identify malicious behavior(e.g., packing, anomalous imports, obfuscation).
Drive Intelligent Protections:Take a security hypothesis, validate it via data analysis, and build Python-based proof-of-concepts that scale into production-grade detections-spanning machine learning classifiers to AI-informed automated rule generation.
Shape the Pipeline: Influence data pipeline strategies and model design by ensuring our datasets and automated logic accurately capture the ground truth of modern threat landscapes.

We are seeking a Senior / Principal Security Researcher to join our high-caliber Security ML Team. Our team solves complex security challenges using disruptive technologies, AI/ML algorithms, and massive datasets to design and develop groundbreaking security solutions that transition directly from research into production-grade protection.
In this role, you will serve as the core security domain expert within a multidisciplinary team, providing essential security-side expertise to assist in the development of ML models, deeplearning models, and Small Language Models (SLMs). By translating complex malware behaviors and static file attributes into actionable logic, your research will directly shape the algorithms that protect millions of endpoints worldwide. If you are looking to autonomously drive high-impact research initiatives from inception to production and use data-informed critical thinking to influence advanced security modeling, we want to hear from you.
Key Responsibilities:
The Bridge to the AI Ecosystem: Serve as the core security domain expert within a multidisciplinary team, translating complex malware behaviors and static file attributes into actionable features, labels, or heuristics-fueling AI algorithms and automated, data-driven security logic.
Telemetry & Sensor Optimization:Analyze raw endpoint telemetry (such as memory buffers, hook outputs, and IPC artifacts) to evaluate algorithm effectiveness and work with AI researchers to tweak or implement new models..
Deconstruct File Behavior: Look past the "black box" of machine learning by digging into executable formats (PE, ELF, Mach-O) and scripts to identify malicious behavior(e.g., packing, anomalous imports, obfuscation).
Drive Intelligent Protections:Take a security hypothesis, validate it via data analysis, and build Python-based proof-of-concepts that scale into production-grade detections-spanning machine learning classifiers to AI-informed automated rule generation.
Shape the Pipeline: Influence data pipeline strategies and model design by ensuring our datasets and automated logic accurately capture the ground truth of modern threat landscapes.

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.

We are seeking a visionary and highly technical Principal / Sr. Principal Security Researcher to join our security research team. In this role, you will be at the forefront of innovating automated defense systems to rapidly protect platform customers against advanced cyber threats at an unprecedented scale. This position offers a unique opportunity to blend deep traditional cybersecurity expertise - including OS internals, reverse engineering, and advanced detection engineering with cutting-edge AI technologies like LLMs, SLMs, and agentic workflows.
You will spearhead the creation of innovative prevention solutions, leveraging massive streams of agent telemetry to design AI-driven logic that neutralizes threats before they execute. As a key technical leader, you will partner closely with top-tier data scientists and product engineers to translate cutting-edge security research into production-grade capabilities, ensuring we stay ahead of the evolving threat landscape.
Key Responsibilities
Develop Automated Defense Systems:Create, engineer, and deploy automated solutions for the prevention and detection of advanced cyber threats, analyzing complex data to rapidly protect platform customers at scale.
Innovate with AI:Partner closely with data scientists to leverage LLMs, SLMs & deeplearning techniques to fuel these advanced prevention solutions and automated defense capabilities.
Enhance Palo Alto Networks Agentix:Research, develop, and continuously improve the Agentix solution. Drive the development of next-generation security content by designing and implementing specialized AI agents to automate security operations and workflows.
Drive Security Innovations:Spearhead new research initiatives from the ground up. Act as the primary driver across key stakeholders, leading top-tier data scientists and engineers to ensure the successful delivery of enterprise-grade security capabilities.

Required Principal / Sr. Principal Security Research - Advanced Cyber Research (Cortex)
We are seeking a visionary and highly technical Principal / Sr. Principal Security Researcher to join our security research team. In this role, you will be at the forefront of innovating automated defense systems to rapidly protect platform customers against advanced cyber threats at an unprecedented scale. This position offers a unique opportunity to blend deep traditional cybersecurity expertise - including OS internals, reverse engineering, and advanced detection engineering with cutting-edge AI technologies like LLMs, SLMs, and agentic workflows.
You will spearhead the creation of innovative prevention solutions, leveraging massive streams of agent telemetry to design AI-driven logic that neutralizes threats before they execute. As a key technical leader, you will partner closely with top-tier data scientists and product engineers to translate cutting-edge security research into production-grade capabilities, ensuring we stay ahead of the evolving threat landscape.
Key Responsibilities:
Develop Automated Defense Systems:Create, engineer, and deploy automated solutions for the prevention and detection of advanced cyber threats, analyzing complex data to rapidly protect platform customers at scale.
Innovate with AI:Partner closely with data scientists to leverage LLMs, SLMs & deeplearning techniques to fuel these advanced prevention solutions and automated defense capabilities.
Research, develop, and continuously improve the Agentix solution. Drive the development of next-generation security content by designing and implementing specialized AI agents to automate security operations and workflows.
Drive Security Innovations:Spearhead new research initiatives from the ground up. Act as the primary driver across key stakeholders, leading top-tier data scientists and engineers to ensure the successful delivery of enterprise-grade security capabilities.

Shape the future of AI-powered software engineering at Palo Alto Networks. As part of our AI Transformation group, youll join a multidisciplinary group building state-of-the-art, agentic AI systems that directly elevate the productivity of thousands of internal engineers.
We build internal AI infrastructure, frameworks, agents, harnesses, methodologies, and adoption programs powered by cutting-edge LLMs. Whether you are researching novel AI paradigms, architecting platform infrastructure, engineering end-to-end agentic tools, or driving developer enablement, your work will redefine how software at Palo Alto Networks gets built at scale.
This is an applied AI research role, where you will be inventing new technology, bringing the latest innovations into our agentic software development practices, and responsible for co-building systems that get deployed to our entire, global Cortex engineering organization.
Key Responsibilities
Stay at the forefront of AI advancements in agentic coding and integrate state-of-the-art techniques.
Build functional Proof of Concepts (PoCs) and architectural skeletons to evaluate new AI techniques before scaling.
Critically audit and challenge internal AI solutions, benchmarks, and architectures to prevent technological obsolescence.
Design rigorous testing methodologies to assess model accuracy, latency, cost efficiency, and drift across solutions.
Research and design advanced knowledge-retrieval architectures, including standard and graph-based RAG and hybrid contextual search.
Collaborate with core AI engineering to transition validated prototypes into reusable components for our engineering workforce.
Coordinate closely with the US Foundational AI Research team via flexible evening Israel / morning US meetings.

Were looking for an experienced Vulnerability Researcher to help us uncover how modern AI tools, agents, and enterprise environments can be abused - and turn those findings into impactful security research.
This role combines deep technical research with real industry impact.
Youll investigate emerging attack techniques, build proof-of-concepts, publish research the security community cares about, and help shape how our company protects customers.
Were looking for someone who loves understanding how things work, thinks creatively like an attacker, and knows how to turn technical findings into research people actually want to read and talk about.
What Youll Do
Research vulnerabilities and attack techniques across AI tools, endpoints, browsers, MCP servers, extensions, and enterprise environments
Investigate real-world threats, CVEs, supply-chain attacks, and AI-related security risks
Build proof-of-concepts and demonstrations of new attack paths
Publish technical research, blog posts, and security content
Work closely with Product and Engineering to improve our companys detection and prevention capabilities
Help position our company as a leading company in AI security research
Explore new technologies and identify risks before they become mainstream.

We're looking for an Experienced Performance Researcher to join our founding team. Youll be responsible for building and optimizing scalable cloud infrastructure solutions tailored for AI workloads. This role offers a unique opportunity to directly shape our infrastructure strategy, improve system reliability and performance, and contribute to establishing us as a leader in adaptive AI compute management.
Join us to tackle the magic that make AI tick under the hood and build the backbone powering the AI revolution.
What Youll Do
- Design and build high-performance distributed inference pipelines for LLMs, focused on large-batch, non-real-time scenarios.
- Optimize GPU memory usage, kernel execution, and communication across nodes (NCCL, MPI, etc.).
- Own CUDA kernels, compiler-level tricks, and multi-GPU scheduling logic.
- Lead profiling and performance tuning for throughput, and cost- down to the kernel level.
- Collaborate with infra, product, and research teams to define SLAs, resource allocation logic, and runtime behaviors.
- Help build the core infrastructure that will run LLM workloads across hybrid GPU environments (cloud/on-prem/self-hosted).

We're looking for an AI researcher to take an integral part in research into how these models behave, how they should be evaluated, and how they can be deployed and used more efficiently across real engineering workloads.
This is a deeply technical research role with direct product impact.
You'll study frontier and open-source models, develop evaluation frameworks, investigate inference and model optimization techniques, explore local deployment strategies, and help answer questions such as:
Which model should handle a particular task?
How much capability do we lose when we quantize it?
Can a smaller local model replace a frontier API for a specific workload?
How should models be routed across latency, cost, privacy, and quality constraints?
How do we measure whether one model is actually better than another for agentic software engineering?
Your work will directly shape model strategy and the intelligence behind our AI infrastructure products.

We are looking for a talented AI Applied Researcher to help us develop advanced AI solutions that will empower impactful projects. The Data Science team leads the AI research and innovation efforts of the company, and is focused on pushing AI boundaries to enhance the product and optimize processes.
What Youll Do:
Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions
Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails and audit trails.
Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback.
Collaborate with engineering teams to design, build, and maintain production pipelines.
Stay up to date with the latest developments in AI, machine learning, and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services.