We're looking for a Senior Applied AI Scientist to sit at the frontier of AI security - turning emerging threats into the detection models that protect how AI is used inside the world's largest organizations. You'll be part of the AI Security Research department, working hand-in-hand with security researchers to translate threat intelligence into trainable signals that catch malicious behavior and security risks across the AI-powered workflows of Fortune 500 companies.

You'll bring deep technical versatility - reaching for classical ML, deep learning, or agentic based approaches based on what the problem demands, and the evaluation rigor to know when a model is truly ready for the real world. If you want to define what AI security engineering looks like, not just practice it, this role is for you.

What Youll Do
Responsibilities:
Build, train, and ship detection models end-to-end, from raw data to production.
Choose the right method for each problem - traditional ML, deep learning, fine-tuned LLMs, agents or heuristics - based on theoretical insights turned into practical results.
Partner with security researchers to turn security research outputs and domain expertise into detection capabilities.
Own evaluation: design benchmarks, build labeled datasets, and define production standards.
Monitor models in production across all paradigms - ML, deep learning, LLM-based, and agentic systems to track degradation and ensure reliability
Iterate fast, with a tight feedback loop between model performance and product outcomes.

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.

As a Senior Data Scientist on the AI Research & Reliability team, you will be a driving force in shaping the future of our company AI. You will act as a technical leader, working with cutting-edge LLMs, NLP, and machine learning to tackle our most ambiguous and complex customer problems. Working alongside Product, Engineering, and Data Scientist, you will spearhead the architecture, evaluation, and deployment of enterprise-grade AI capabilities at scale, while elevating the technical standards of the team.
You'll Own
The AI Technical Strategy: Lead the AI product lifecycle by partnering deeply with Product and Engineering to translate complex business needs into scalable, state-of-the-art AI solutions. Define the overarching AI approach, agent architectures, success metrics, and long-term technical vision before implementation.
Advanced Agentic Systems: Architect, build, and optimize complex sub-agents, tool-use mechanisms, retrieval systems, and memory architectures that power our company AI Agents. Establish industry-leading evaluation frameworks and benchmarks to rigorously measure and continuously improve workflow reliability.
Conversational Intelligence at Scale: Pioneer new NLP- and LLM-based methodologies to analyze massive, unstructured conversation datasets. You will design approaches that capture the deep intent, nuance, and strategic signals within human interactions.
Production-Grade Model Engineering: Architect highly robust and scalable Python pipelines. Set the standard for creating proprietary datasets, training/fine-tuning models, and integrating LLM-powered solutions into production environments serving millions of critical customer interactions.
You'll Solve
Complex Business Context Reasoning: Designing AI systems that can autonomously reason over vast, unstructured data spaces-combining conversations, CRM signals, and diverse data sources to uncover high-level insights and drive executive decision-making.
Architecting Intelligent Agent Experiences: Solving the hardest architectural challenges around long-term memory, multi-step reasoning, retrieval accuracy (RAG), and deterministic evaluation to ensure our company AI Agents deliver flawless, context-aware assistance.
Extracting Actionable Intelligence: Pushing the boundaries of applied NLP and LLMs to understand deep customer dynamics, foresee market trends, and transform raw, noisy conversations into structured, actionable intelligence across the customer lifecycle.
Advancing Applied AI Innovation: Leading experimentation with state-of-the-art AI approaches (advanced RAG architectures, parameter-efficient fine-tuning, complex agentic workflows) to solve novel product challenges and drastically improve AI quality and reliability.
You'll Impact
Global Sales Transformation: The foundational AI architectures you build will directly empower thousands of enterprises, fundamentally changing how revenue teams operate, strategize, and close deals.
Strategic Innovation to Implementation: You will bridge the gap between academic/bleeding-edge NLP developments and enterprise application, translating complex research into high-quality, scalable code that maintains our company's position as an AI industry leader.

Are you passionate about harnessing cutting-edge data science techniques to protect the world from cyber threats? Do you thrive in the dynamic world of cybersecurity? If so, we invite you to join our innovative and forward-thinking team at our company, where you'll have the opportunity to shape the future of cybersecurity and impact millions of customers.
As a Senior Principal Data Scientist, you will be a technical leader and hands-on architect, bridging the worlds of advanced data science, robust software engineering, and next-generation AI. You will bring a deep, diverse background in classical machine learning algorithms alongside cutting-edge LLM agent architectures to build resilient, production-grade defense techniques against cyber-villains. Operating as a premier technical authority, you will drive the vision, design, and large-scale development of our groundbreaking, Agentix LLM-based security solutions that block attacks even before they begin.
Key Responsibilities
Serve as a hands-on technical compass for a diverse, elite product-oriented research team, pioneering state-of-the-art technologies and setting the engineering standards for AI/ML excellence across the organization.
Design, implement, and optimize robust Agentic LLM solutions and multi-agent workflows engineered to autonomously counter modern, sophisticated cyber threats.
Oversee and actively contribute to the entire end-to-end lifecycle, moving seamlessly from ambiguous research concepts and POCs to high-throughput, low-latency production deployments.
Build and enforce comprehensive frameworks for continuous real-time monitoring, evaluation, and guardrails to track model drift, latency, and agent behavior in production environments.
Decompose highly complex, multi-layered algorithmic problems into actionable technical roadmaps and strategic insights for both deeply technical engineers and executive business stakeholders.

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.

Are you passionate about harnessing cutting-edge data science techniques to protect the world from cyber threats? Do you thrive in the dynamic world of cybersecurity? If so, we invite you to join our innovative and forward-thinking team at Palo Alto Networks, where you'll have the opportunity to shape the future of cybersecurity and impact millions of customers.
As a Senior Principal Data Scientist, you will be a technical leader and hands-on architect, bridging the worlds of advanced data science, robust software engineering, and next-generation AI. You will bring a deep, diverse background in classical machine learning algorithms alongside cutting-edge LLM agent architectures to build resilient, production-grade defense techniques against cyber-villains. Operating as a premier technical authority, you will drive the vision, design, and large-scale development of our groundbreaking, Agentix LLM-based security solutions that block attacks even before they begin.
Key Responsibilities
Serve as a hands-on technical compass for a diverse, elite product-oriented research team, pioneering state-of-the-art technologies and setting the engineering standards for AI/ML excellence across the organization.
Design, implement, and optimize robust Agentic LLM solutions and multi-agent workflows engineered to autonomously counter modern, sophisticated cyber threats.
Oversee and actively contribute to the entire end-to-end lifecycle, moving seamlessly from ambiguous research concepts and POCs to high-throughput, low-latency production deployments.
Build and enforce comprehensive frameworks for continuous real-time monitoring, evaluation, and guardrails to track model drift, latency, and agent behavior in production environments.
Decompose highly complex, multi-layered algorithmic problems into actionable technical roadmaps and strategic insights for both deeply technical engineers and executive business stakeholders.

As an AI Expert at our company, youll take full ownership of AI-powered product capabilities - from concept to production. Youll work closely with Product, Engineering, and Security domain experts to build practical, reliable AI systems that improve how teams operate and secure cloud environments. This is an applied role: we care about shipping, adoption, and measurable outcomes. Youll engage with users, test MVPs in production, iterate quickly based on feedback, and make sure what you build holds up in the real world. And yes youll also jump in as a Support Hero when needed, helping customers succeed and learning directly from how they work.
Key Responsibilities
Build and ship AI features that improve cloud security operations (e.g., control recommendations, drift detection explanations, guided remediation, policy generation, investigations, workflow automation).
Design and implement AI agents tuned for cloud-security tasks, including the surrounding framework (tools, permissions, orchestration, guardrails, and automation).
Apply deep understanding of cloud security domains (IAM, network controls, logging/telemetry, posture management, governance, misconfiguration, threat scenarios) to guide product decisions and ensure the AI behaves safely and correctly.
Integrate with multi-cloud APIs and security controls (AWS/Azure/GCP/OCI), building end-to-end flows from user intent → actionable outcome. Create and maintain evaluation methods for model quality (accuracy, coverage, hallucination rates, latency, cost, and user satisfaction) and build tooling to continuously measure performance in production.
Build data and feedback loops to keep systems relevant over time (user corrections, outcome tracking, regression testing, prompt/model iteration).
Stay current with practical advancements in LLMs/agents and engineering patterns, and adopt whats useful (not hype) into production.

we are looking for a AI Engineer - Algorithm Team.
As an AI Engineer, you will join a fast-moving, highly technical team that works at the intersection of computer vision, deep learning, and modern AI. You will be the driving force behind our LLM and agentic AI efforts - exploring, evaluating, and deploying the latest research and tooling in this rapidly evolving space, and shaping how we apply it across the organization to turn cutting-edge ideas into production-ready tools and agents.
You will design and build LLM-powered applications, agentic workflows, and internal tools that empower our algorithms, mapping, and engineering teams to move faster and operate at greater scale. Collaboration is central to the role, you will work closely with researchers, engineers, and domain experts to identify high-impact opportunities, prototype quickly, and integrate reliable AI systems into real-world products.
Key Responsibilities:
Design, build, and iterate on LLM-powered applications, including retrieval-augmented generation (RAG) systems, agents, and fine-tuned models tailored to unique data and workflows.
Develop agentic workflows that automate complex, multi-step tasks across research, data analysis, and engineering pipelines.
Build internal tools and assistants that empower algorithm researchers, mapping experts, and engineers to work faster and more effectively.
Evaluate and integrate the latest foundation models, frameworks, and techniques (e.g., prompt engineering, fine-tuning, tool use, multi-agent orchestration), keeping pace with rapid advances in the field.
Design robust evaluation methodologies to measure quality, reliability, and safety of LLM-based systems.
Collaborate closely with the Algorithms, Mapping, and Software teams to identify high-impact opportunities and transition prototypes into reliable, production-grade systems.

Were looking for a hands-on AI Engineer to build and own the agentic workflows at the heart of our security intelligence engine.
This is a backend-focused engineering role: youll design, build, and maintain the autonomous systems that execute security workflows end-to-end - taking capabilities from research prototype to scalable, production-grade infrastructure.
Youll be working at the edge of applied AI, turning LLMs and agentic frameworks into reliable, observable systems that operate in real customer environments.
What Youll Build:
Agentic Workflows (Core Focus): Design and maintain the orchestration backbone for multi-step, autonomous agents that investigate, reason about, and act on complex security operations.
Internal AI Infrastructure: Contribute to a shared platform for models, data pipelines, training, evaluation, and observability that the whole AI team builds on.
Responsibilities:
Build and maintain the agentic workflow engine - orchestration, tool use, state management, retries, and evaluation - that powers our AI-driven security features.
Develop the backend services and APIs that deploy AI capabilities safely and at scale.
Collaborate with AI Researchers to translate findings into production-grade autonomous workflows.
Own reliability, observability, and performance of the agentic systems in production.

Were looking for a Data scientist Expert to join us and spread our power. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems. You will work closely with cross-functional teams to explore, innovate, and implement AI-driven solutions to tackle emerging threats, examine cloud security features, and enhance the companys security posture.
Responsibilities:
Lead applied research on AI agents and LLM-driven features in the platform - from autonomous threat investigation agents to AI-powered security operations workflows.|Cover a range of features - from leveraging LLMs to enhance customer investigation experience to novel usage of AI for cloud security.
Collaborate with engineering teams to design, build, and maintain production pipelines.
Work closely with the Security Research and Product teams to define research goals
Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments.
Stay abreast of cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions' accuracy, efficiency, and scalability.