Senior AI Researcher - Agentic Endpoint Security(Cortex) at Palo Alto Networks

Tel Aviv, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

19 Sep, 26

Salary

0.0

Posted On

21 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Agents, LLMs, Python, Autonomous Systems, Cybersecurity, Multi-agent Orchestration, Retrieval Augmented Generation, Inference Optimization, Malware Analysis, Vulnerability Research, Prompt Engineering, Distributed AI Systems, Threat Hunting, Adversarial Scenarios, Evaluation Harnesses, Observability Systems

Industry

Computer and Network Security

Description

Our Mission At Palo Alto Networks®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place. Who We Are In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us! We believe collaboration thrives in person. That’s why most of our teams work from the office full time, with flexibility when it’s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes. Job Summary We are hiring an AI Researcher to join the research team building the next generation of AI-native security systems. You will work alongside security and threat researchers to build large-scale AI agents that reason over software, code, endpoint activity, and security signals to detect malicious behavior, uncover vulnerabilities, assess risk, and make autonomous security decisions in real-world production environments. We are entering the Mythos era - where attackers operate at machine speed using autonomous systems and AI-generated software, and defenders must evolve the same way. We use state-of-the-art frontier models, including access to Mythos, to build reliable AI-native security systems at global scale. You will help design the evaluations, harnesses, and reliability infrastructure that make autonomous agents dependable under real customer load, while collaborating with leading AI organizations including Anthropic on initiatives such as Glasswing. This is an opportunity to work at the frontier of AI, autonomous systems, and cybersecurity while helping define how the next generation of security systems will operate. Key Responsibilities Build AI agents and autonomous security systems that reason over software, code, endpoint activity, MCPs, and security signals to detect malicious behavior, uncover vulnerabilities, and assess risk at production scale. Develop systems, tooling, and infrastructure that enable agents to autonomously investigate threats, hunt for malware in massive datasets, and operate reliably in complex security environments. Design and run experiments to evaluate frontier-model and agent capabilities in realistic adversarial scenarios, including benchmark creation, large-scale datasets, automated evaluations, and human-in-the-loop review systems. Build the evaluation harnesses, observability systems, and reliability infrastructure required to make autonomous agents accurate, scalable, and dependable under real customer load. Engineer for scale and performance across large distributed AI systems, including inference optimization, orchestration, batching, caching, cost controls, and graceful degradation under high demand. Continuously evaluate emerging models, agent architectures, prompting techniques, and research directions to ensure our systems remain at the frontier of AI-native cybersecurity. Rapidly prototype and test new approaches across reasoning, autonomy, evaluations, and security workflows as the AI landscape evolves. Partner closely with threat and security researchers to extract domain expertise, translate analyst reasoning into AI workflows, and enable new forms of automation and autonomous investigation. Collaborate with leading AI and security researchers to shape the future of AI-native cybersecurity as the industry transitions into the Mythos era. Senior candidates will help define research direction, shape technical strategy, identify high-leverage problems, and influence how autonomous AI systems are deployed across the organization. Qualifications Required Qualifications Strong experience building and operating AI agents or autonomous systems in production environments. Hands-on experience with LLMs, agent frameworks, tool use, reasoning systems, retrieval, evaluations, or multi-agent orchestration. Proven ability to rapidly design experiments, iterate on ideas, and turn research into reliable production systems. Deep familiarity with the rapidly evolving AI ecosystem; enthusiasm for continuously experimenting with new models, techniques, architectures, and research directions. Strong intuition for identifying which new AI capabilities are production-ready versus hype, and ability to quickly translate frontier advances into practical systems. Strong engineering skills, especially in Python and modern AI infrastructure. Proven ability to own problems end-to-end, from research and prototyping through deployment, scaling, and reliability. Enthusiasm for building AI-native systems that reason over software, code, and security signals in real-world environments. Collaborative mindset; ability to work effectively alongside AI researchers, engineers, and security experts. Motivation to tackle hard, ambiguous, high-impact problems at the frontier of AI systems. Preferred Qualifications Background in cybersecurity, malware analysis, vulnerability research, detection systems, or adversarial environments. Experience applying LLMs or autonomous agents to cybersecurity problems. Strong intuition around adversarial behavior, evasions, model failures, and evolving attack techniques. Background in offensive security research, pentesting, exploit development, or threat hunting. Track record in CTFs, bug bounties, open-source security tooling, or security research. Experience building evaluation systems, benchmarks, or datasets for AI or security systems at scale. Our Commitment We’re trailblazers that dream big, take risks, and challenge cybersecurity’s status quo. It’s simple: we can’t accomplish our mission without diverse teams innovating, together. We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at accommodations@paloaltonetworks.com. Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics. All your information will be kept confidential according to EEO guidelines. Is role eligible for Immigration Sponsorship? No. Please note that we will not sponsor applicants for work visas for this position. 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Responsibilities

Develop and scale AI agents and autonomous security systems to detect malicious behavior and uncover vulnerabilities in production environments. Design evaluation frameworks and reliability infrastructure to ensure AI-native security systems operate dependably at global scale.