Senior Principal Data Scientist - LLM Agents (Cortex)
Palo Alto Networks
Senior Principal Data Scientist - LLM Agents (Cortex)
Job Description
Our MissionAt 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 AreIn 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 SummaryAre 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 ResponsibilitiesServe 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.Qualifications Required QualificationsA proven track record as an experienced architect who leads by example, capable of writing core, production-critical code, conducting rigorous architecture reviews, and mentoring senior technical staff.At least 3 years of hands-on experience building, scaling, and optimizing Agentic LLM systems. This includes deep familiarity with common frameworks (e.g., LangChain, LangGraph, AutoGen) and a sophisticated understanding of tool-use optimization, memory management, and deterministic behavioral alignment.At least 5 additional years of deep experience in data science, with expert-level command of classical machine learning algorithms applied to complex, real-world data landscapes.At least 5 additional years of experience as a software engineer with high proficiency in Python and querying languages. You possess deep knowledge of software design patterns, concurrency, CI/CD pipelines, and writing clean, scalable, maintainable code.BSc in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or a related field from a top university. An advanced degree is highly preferred. Demonstrated expertise in deploying and operating ML/LLM workloads at enterprise scale. You have a comprehensive understanding of containerization (Docker, Kubernetes), high-throughput data pipelines, and proactive system monitoring.Exceptional ability to run end-to-end research-to-production initiatives, showcasing an analytical mindset capable of translating raw data into highly accurate, real-time defensive actions.Extensive, hands-on experience utilizing, fine-tuning, and optimizing open-source generative AI frameworks and libraries (e.g., Hugging Face, PyTorch, vLLM, DeepSpeed) to build and deploy high-performance models.Proven experience architecting data solutions and working within major cloud and big data ecosystems (e.g., GCP, AWS, Snowflake) to ingest, process, and analyze high-velocity, petabyte-scale datasets.Outstanding communication and presentation skills, with a demonstrated ability to align cross-functional engineering, product, and research teams toward unified technical goals.Preferred QualificationsMSc/PhD in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or a related field from a top university.Background in the cybersecurity domainOur 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.
Locations
- Office - Israel - Tel Aviv
Skills Required
- common frameworksintermediate
- data scienceintermediate
- Pythonintermediate
- software design patternsintermediate
- deployingintermediate
- cybersecurity domainintermediate
Required Qualifications
- A proven track record as an experienced architect who leads by example, capable of writing core, production-critical code, conducting rigorous architecture reviews, and mentoring senior technical staff. (experience)
- At least 3 years of hands-on experience building, scaling, and optimizing Agentic LLM systems. This includes deep familiarity with common frameworks (e.g., LangChain, LangGraph, AutoGen) and a sophisticated understanding of tool-use optimization, memory management, and deterministic behavioral alignment. (experience, 3 years)
- At least 5 additional years of deep experience in data science, with expert-level command of classical machine learning algorithms applied to complex, real-world data landscapes. (experience)
- At least 5 additional years of experience as a software engineer with high proficiency in Python and querying languages. You possess deep knowledge of software design patterns, concurrency, CI/CD pipelines, and writing clean, scalable, maintainable code. (experience)
- BSc in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or a related field from a top university. An advanced degree is highly preferred. (degree in machine learning)
- Demonstrated expertise in deploying and operating ML/LLM workloads at enterprise scale. You have a comprehensive understanding of containerization (Docker, Kubernetes), high-throughput data pipelines, and proactive system monitoring. (experience)
- Exceptional ability to run end-to-end research-to-production initiatives, showcasing an analytical mindset capable of translating raw data into highly accurate, real-time defensive actions. (experience)
- Extensive, hands-on experience utilizing, fine-tuning, and optimizing open-source generative AI frameworks and libraries (e.g., Hugging Face, PyTorch, vLLM, DeepSpeed) to build and deploy high-performance models. (experience)
- Proven experience architecting data solutions and working within major cloud and big data ecosystems (e.g., GCP, AWS, Snowflake) to ingest, process, and analyze high-velocity, petabyte-scale datasets. (experience)
- Outstanding communication and presentation skills, with a demonstrated ability to align cross-functional engineering, product, and research teams toward unified technical goals. (experience)
- A proven track record as an experienced architect who leads by example, capable of writing core, production-critical code, conducting rigorous architecture reviews, and mentoring senior technical staff. (experience)
- At least 3 years of hands-on experience building, scaling, and optimizing Agentic LLM systems. This includes deep familiarity with common frameworks (e.g., LangChain, LangGraph, AutoGen) and a sophisticated understanding of tool-use optimization, memory management, and deterministic behavioral alignment. (experience, 3 years)
- At least 5 additional years of deep experience in data science, with expert-level command of classical machine learning algorithms applied to complex, real-world data landscapes. (experience)
- At least 5 additional years of experience as a software engineer with high proficiency in Python and querying languages. You possess deep knowledge of software design patterns, concurrency, CI/CD pipelines, and writing clean, scalable, maintainable code. (experience)
- BSc in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or a related field from a top university. An advanced degree is highly preferred. (degree in machine learning)
- Demonstrated expertise in deploying and operating ML/LLM workloads at enterprise scale. You have a comprehensive understanding of containerization (Docker, Kubernetes), high-throughput data pipelines, and proactive system monitoring. (experience)
- Exceptional ability to run end-to-end research-to-production initiatives, showcasing an analytical mindset capable of translating raw data into highly accurate, real-time defensive actions. (experience)
- Extensive, hands-on experience utilizing, fine-tuning, and optimizing open-source generative AI frameworks and libraries (e.g., Hugging Face, PyTorch, vLLM, DeepSpeed) to build and deploy high-performance models. (experience)
- Proven experience architecting data solutions and working within major cloud and big data ecosystems (e.g., GCP, AWS, Snowflake) to ingest, process, and analyze high-velocity, petabyte-scale datasets. (experience)
- Outstanding communication and presentation skills, with a demonstrated ability to align cross-functional engineering, product, and research teams toward unified technical goals. (experience)
Preferred Qualifications
- MSc/PhD in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or a related field from a top university. (degree in machine learning)
- Background in the cybersecurity domain (experience)
- MSc/PhD in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or a related field from a top university. (degree in machine learning)
- Background in the cybersecurity domain (experience)
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.
- 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.
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