דרושים » AI » AI Researcher

we are looking for a Research Engineer
As a research engineer , you'll be at the forefront of building systems to evaluate and secure frontier AI models. You'll work on infrastructure and experiments to assess model capabilities, implement agent frameworks, and develop mitigations for advanced AI systems. Your role will involve creating robust evaluation pipelines, developing security-focused testing frameworks, and building tools that help understand and mitigate risks related to frontier models. Youll have a chance to understand the research context and your codes impact and contribute as a meaningful part of a growing team.
Representative projects:
Building a tool to continuously evaluate models and mitigate their risks. From designing the APIs for frontier labs, to building analysis and visualization tools that summarize 10,000+ transcripts into specific conclusions.
Designing and building challenges that measure a models ability to evade discovery, allowing us to see if models can operate on remote systems while avoiding detection by common defensive security tools.
Developing controlled environment frameworks for more secure use of frontier models.
Designing and building agents that improve a models ability to complete complex tasks. Includes many potential avenues, such as incorporating SOTA prompting practices, creating tools for task delegation, and more.
Publishing your research and/or delivering research to our customers.

We are looking for a Principal AI Security Researcher with deep, hands-on expertise in AI red teaming and AI security to lead and scale RLGyms AI security research efforts.
This is not a traditional cybersecurity leadership role. We need someone who has directly worked on breaking, attacking, testing, and securing AI systems, particularly large language models (LLMs), generative AI applications, and agentic AI systems.
The ideal candidate has significant practical experience designing and executing AI red-team programs, developing adversarial attacks, identifying AI-specific vulnerabilities, building automated red-teaming capabilities, and translating findings into effective guardrails and security protections.
What you'll be doing:
Lead and scale multidisciplinary teams focused on AI red teaming, adversarial testing, and AI security research.
Design and execute sophisticated attacks against LLMs, GenAI applications, and agentic AI systems.
Research attack techniques including prompt injection, jailbreaks, indirect prompt injection, tool abuse, agent manipulation, data leakage, model misuse, and adversarial behavior.
Build and evolve AI red-teaming engines and automated adversarial testing systems, including RLGym.
Building and scaling global AI security teams (red teaming, adversarial research, guardrails engineering) while fostering an innovation-driven security culture.
Overseeing advanced adversarial evaluations for GenAI models, agentic AI, and multi-agent (A2A) systems
Defining and implementing AI red-teaming frameworks aligned with OWASP AI Security guidelines, MITRE ATLAS, and NIST AI RMF, and operationalizing automated red-team engines to continuously stress-test models at scale.
Partnering with product and engineering to design and deploy enterprise-ready AI guardrails - including policy enforcement layers, monitoring pipelines, and anomaly detection systems - and championing secure deployment practices for GenAI (including agent orchestration via MCP and A2A workflows).

We are seeking a Senior AI Engineer to join core product organization, where you will design, build, and scale next-generation AI systems powering real-world cybersecurity use cases across our diverse product portfolio (Posture, Detection, and CTI). This role focuses on developing production-grade systems leveraging LLMs, advanced machine learning, and agent-based architectures.
You will join a team within Cyber R&D organization-leading the companys core product portfolio- while driving AI innovation and establishing engineering best practices across the domain. The team focuses on building and optimizing large-scale AI systems, including LLM-based solutions and advanced multi-agent workflows, working closely with data scientists and researchers to bring ideas into production.
The Responsibilities:
Design, build, and own end-to-end AI solutions- from data collection and preprocessing to model training, evaluation, and production deployment.
Optimize systems for performance, scalability, and reliability in production environments.
Collaborate closely with product, design, and engineering teams to identify and deliver AI-driven capabilities that address real customer needs.
Stay up to date with emerging AI/ML technologies, frameworks, and best practices, and apply them where they create real impact.
Work across the stack, contributing to backend systems and data pipelines that support large-scale AI applications.
Troubleshoot and resolve complex system issues, including performance bottlenecks, race conditions, and memory-related challenges.
Approach problems with a strong analytical mindset, delivering robust solutions while contributing to a high-performing, collaborative team environment.

We are looking for an AI Researcher to help build the intelligence behind our AI security platform.

This is a hands-on research role focused on understanding how modern large language models and AI agents behave, identifying new attack vectors and protection techniques, and translating cutting-edge research into production-ready capabilities. The intelligence developed by this team is a core differentiator of our platform and a key driver of the company's success.

You will work at the intersection of machine learning, LLMs, and cybersecurity, partnering closely with AI engineers and product teams to develop technologies that directly power our product. We're looking for someone who enjoys understanding how neural networks and foundation models work, pushes the boundaries of AI research, and is excited to see their work deployed into production and used by customers.

What you will do
Research the behavior, capabilities, and limitations of modern large language models and AI agents.
Design novel techniques for detecting, evaluating, and proactively protecting against AI threats, prompt injection, model misuse, and emerging attack vectors.
Develop new approaches for securing AI systems and improving the intelligence that powers our platform.
Design and run experiments to evaluate model behavior, validate new ideas, and measure the effectiveness of protection techniques.
Build research prototypes and turn them into production-ready capabilities.
Work closely with Product and Engineering to translate research into scalable product features.
Stay current with advances in LLMs, foundation models, post-training techniques, AI security, and AI safety.
Contribute to the long-term technical direction of our AI security platform.

we are looking for a Senior Software Engineer.
As a Software Engineer , you will take ownership of designing, building, and scaling the production systems that power our evaluation and security platform for frontier AI models.
Your work will focus on creating robust, resilient, and high-performance infrastructure-whether thats distributed pipelines, backend services, or tooling that supports our research teams.
This role is engineering-first with a strong research and cyber component. You will develop systems that must run reliably in production, integrate with external partners, and support large-scale data, experiments, and automated evaluations. Youll drive architectural decisions, lead technical implementations, and shape how our platform evolves.
Representative Responsibilities:
Architecting and scaling production-grade systems and workflows.
Building backend services, APIs, and monitoring tools for large-scale model evaluations.
Designing infrastructure that supports research experiments at scale.
Implementing agent frameworks in production environments
Designing and building challenges that measure a models ability to evade discovery, allowing us to see if models can operate on remote systems while avoiding detection by common defensive security tools.

Required Sr. Principal AI Researcher, AI Transformation
Job Summary
Shape the future of AI-powered software engineering. 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 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.

We are seeking a Senior AI Researcher to lead post-training evaluation, red-teaming, and reinforcement learning (RL) gym audits on open-weight models. The ideal candidate will establish rigorous benchmarking methodologies, evaluate large language models (LLMs) against complex threats like Indirect Prompt Injections (IPI), and construct post-training evaluation pipelines that accurately measure realistic frontier-level security capabilities. Key Responsibilities RL Post-Training & Benchmarking: Execute post-training runs (e.g. GRPO) using mainstream open-weight generalist models against security-focused RL environments, targeting threat vectors like Indirect Prompt Injection (IPI). Reward Diagnostics & Trace Analysis - Analyze live loss curves and rollout traces to identify reward hacking, lazy policy convergence, and flawed or over/under-specified verifiers. Task & Environment Auditing: Review tasks and multi-turn environments (including tool use, web navigation, and computer use) for realism, threat model accuracy, data distribution, and dataset balance. Performance Reporting (Gym Cards): Generate comprehensive evaluation cards detailing hill-climbing performance uplift across checkpoints, failure modes, tokens/turns per rollout, and task-level success rates. Integration & Orchestration: Integrate dockerized environments (e.g., Harbor format) into internal training frameworks, optimizing reset/statefulness semantics, concurrency, and throughput ceilings.
About us:
we are a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, our company provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. we are widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

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.

We are seeking a visionary and hands-on Staff AI Scientist to help shape the next generation of foundational language models and agentic systems that empower small and medium-sized businesses to thrive. In this role you will define, design, and build groundbreaking AI solutions that understand, reason, and act across complex financial and business contexts.
You will collaborate closely with cross-functional experts across AI research, data science, engineering, and product to create intelligent agents that help SMBs automate financial tasks, make smarter decisions, and operate more efficiently. Your work will combine scientific rigor with visionary execution, balancing theoretical innovation with large-scale practical impact.
As a Staff Scientist you set technical direction beyond your own projects. You are a builder-scientist - a creative thinker who develops novel model architectures and training paradigms and also drives their implementation and validation in real-world applications - and you raise the scientific bar for the teams around you. You will help shape the AI foundation that powers transformative products serving millions of customers.
Responsibilities:
Set technical direction. Define the technical strategy and roadmap for next-generation agentic and foundation-model systems, and drive innovation and scientific excellence across the organization.
Build foundational models and agents. Design and develop foundational language models and agentic architectures that power intelligent decision-making for small and medium businesses.
Advance the science. Explore novel approaches in large-scale pretraining, fine-tuning (SFT and RLFT/GRPO), retrieval-augmented generation, and reasoning to improve factuality, adaptability, and alignment.
Solve real financial work. Build intelligent agents that understand financial data, customer context, and business workflows - from bookkeeping and autonomous accounting to planning, communication, and insight generation.
Leverage our data moat. Turn our unique ecosystem signals - counterparty behavior, two-sided transaction visibility, and business twins - into defensible modeling advantages.
Ship end-to-end. Take work from experimentation to production, owning evaluation frameworks and metrics that prove real-world impact.
Elevate others. Mentor scientists and engineers, review technical designs, and grow the craft of the wider team - a core expectation at the Staff level.
Collaborate across functions. Partner with AI research, engineering, product, and design to translate breakthrough science into scalable products used by millions.
Share knowledge. Publish and present research findings, internal innovations, or contributions to open-source frameworks where appropriate.

We are looking for a Senior AI Engineer to design and build production-grade, LLM-powered systems. You'll work at the intersection of software engineering and applied AI - shipping agents, RAG pipelines, and tool-using systems that solve real problems at scale. This is a hands-on, high-ownership role for someone who thrives at the frontier of what's possible with modern LLMs and isn't afraid to write the glue, the infrastructure, and the prompts that make it all work.
This is a **cross-functional, company-wide role**. You won't be embedded in a single product team - instead, you'll partner with every department to identify high-leverage opportunities and build AI-powered tools and workflows that boost productivity and efficiency across the entire organization.
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
What You'll Do:
- Design, build, and operate LLM-powered applications, agents, and workflows end-to-end - from prototype to production.
- Architect retrieval, context engineering, and tool-use strategies that make models reliable, accurate, and cost-efficient.
- Integrate LLMs with internal services, third-party APIs, and data stores to automate complex business and engineering workflows.
- Build, evaluate, and continuously improve evaluation harnesses for non-deterministic systems.
- Collaborate closely with product, research, and platform teams to translate ambiguous problems into shipped capabilities.
- Stay ahead of the rapidly evolving LLM ecosystem (models, frameworks, agentic patterns) and bring the best ideas into our stack.