Job 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 Levels we are considering: Sr. Staff and Principal Engineers Location: Santa Clara, CA (Hybrid: 3 days/week on-site at Corporate HQ) Team: AIRS (Artificial Intelligence Runtime Security) About the Team Palo Alto Networks is pioneering the world’s most comprehensive AI security platform through Prisma AIRS —protecting complex ecosystems of AI models, applications, and agents from development through runtime. We are building a brand-new initiative within the AIRS team focused on advancing state-of-the-art AI/ML infrastructure and high-performance, distributed backend systems. We are recruiting senior technical leaders to drive this architecture from the ground up. The Role As a senior technical leader on the AIRS team, you will operate at the intersection of machine learning, cloud security, and AI safety. You will design, build, and deploy high-performance infrastructure and autonomous ML solutions that actively classify threats, tune models, and prevent adversarial attacks at enterprise scale. Key Responsibilities Develop scalable anomaly detection pipelines to monitor cloud environments and AI agent actions, ensuring high efficacy with low false-positive and false-negative rates. Lead SLM (Small Language Model) tuning initiatives, optimizing and fine-tuning models for low-latency, highly accurate edge-cloud security tasks. Drive advanced data classification strategies, applying machine learning, NLP, and deep learning methods to massive structured and unstructured datasets to extract complex threat patterns. Be a technical leader who partners closely with product, security, and cloud engineering teams to integrate these ML solutions seamlessly into production systems. Qualifications Education & Experience: MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related field (or equivalent practical experience) with 8 years of software engineering industry experience, including a minimum of 3 years dedicated to machine learning, NLP, or AI systems. Programming & Frameworks: Deep programming expertise in Python and strong hands-on experience with deep learning frameworks such as PyTorch or TensorFlow. Large/Small Language Models: Proven experience working directly with LLMs/SLMs, advanced prompt engineering, and model fine-tuning techniques. Core ML Systems: Strong, demonstrated background in building and scaling auto-classification and anomaly detection models on massive, real-world datasets. Additional Experience: Adversarial & Model Safety: Demonstrated knowledge of cybersecurity concepts and AI safety vulnerabilities (e.g., prompt injection defense, AI red-teaming, model security). Models & Frameworks: Familiarity with DistilBERT and other open-source classification models. Graph Architectures: Familiarity with large, graph-based datasets and processing techniques. Cloud Infrastructure: Experience with distributed cloud systems (GCP or AWS) and deploying scalable ML inference pipelines at scale. Compensation Disclosure The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here . $163,200.00 - $264,000.00/yr 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?: Yes

Requirements

Must-haves

Levels we are considering: Sr. Staff and Principal Engineers
Location: Santa Clara, CA (Hybrid: 3 days/week on-site at Corporate HQ)
Team: AIRS (Artificial Intelligence Runtime Security)
About the Team
Palo Alto Networks is pioneering the world’s most comprehensive AI security platform through Prisma AIRS —protecting complex ecosystems of AI models, applications, and agents from development through runtime.
Develop scalable anomaly detection pipelines to monitor cloud environments and AI agent actions, ensuring high efficacy with low false-positive and false-negative rates.
Lead SLM (Small Language Model) tuning initiatives, optimizing and fine-tuning models for low-latency, highly accurate edge-cloud security tasks.
Drive advanced data classification strategies, applying machine learning, NLP, and deep learning methods to massive structured and unstructured datasets to extract complex threat patterns.
Be a technical leader who partners closely with product, security, and cloud engineering teams to integrate these ML solutions seamlessly into production systems.
Programming & Frameworks: Deep programming expertise in Python and strong hands-on experience with deep learning frameworks such as PyTorch or TensorFlow.
Large/Small Language Models: Proven experience working directly with LLMs/SLMs, advanced prompt engineering, and model fine-tuning techniques.
Core ML Systems: Strong, demonstrated background in building and scaling auto-classification and anomaly detection models on massive, real-world datasets.
Additional Experience: Adversarial & Model Safety: Demonstrated knowledge of cybersecurity concepts and AI safety vulnerabilities (e.g., prompt injection defense, AI red-teaming, model security).
Models & Frameworks: Familiarity with DistilBERT and other open-source classification models.
Graph Architectures: Familiarity with large, graph-based datasets and processing techniques.
Cloud Infrastructure: Experience with distributed cloud systems (GCP or AWS) and deploying scalable ML inference pipelines at scale.
Compensation Disclosure
$163,200.00 - $264,000.00/yr
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.
All your information will be kept confidential according to EEO guidelines.
Is role eligible for Immigration Sponsorship?: Yes

Nice-to-haves

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Application prep

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Keywords to mirror

aimlmachine learningpythongcpaws

Platform: workday
Effort: long