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 Your Career As a Principal Applied AI Researcher on the Prisma AIRS Runtime Security team, you will serve as a technical visionary and strategic leader shaping the future of AI security. You will partner with executive leadership, product management, UX designers, ML engineers, and cross-functional engineering teams to conceptualize, architect, and deliver enterprise-grade, cutting-edge AI detection and protection solutions for the Prisma AIRS Runtime Security product. You will be at the vanguard of innovation for an industry-defining product in the rapidly evolving space of AI Runtime Security. Your responsibilities will transcend standard model development to lead continuous accuracy, latency, and efficiency optimizations, enabling high-throughput integrations across AI threat detection infrastructure, real-time guardrail pipelines, and partner engineering teams. You will drive technical excellence across the organization, set architectural and research standards, and act as a force multiplier by mentoring other researchers and engineers on the team. Your Impact Cross-Functional Delivery: Lead cross-functional collaboration with Product Management, ML, and Quality Engineering teams to deliver new, enterprise-grade AI security-as-a-service offerings in a timely, predictable fashion. Architectural & Security Problem-Solving: Tackle complex, ambiguous technical challenges across system boundaries, translating high-level product and security vision into resilient, production-ready AI detection models and backend architectures. Performance & Scale Optimization: Proactively identify technical bottlenecks and scaling opportunities, driving continuous performance and efficiency optimizations to maximize throughput, lower inference latency, and streamline compute resource utilization at scale. Modern Engineering Best Practices: Evangelize and implement modern engineering best practices, including agentic coding workflows, reproducible research pipelines, and spec-driven development within the team. Model Serving & Enterprise Infrastructure: Lead the architectural design and execution of large-scale enterprise systems with high-performance model serving infrastructure, ensuring seamless, scalable integration across backend security services and partner engineering teams. Mentorship & Technical Excellence: Mentor senior and junior engineers and researchers, fostering a culture of technical excellence, algorithmic rigor, and continuous learning within the team. Qualifications Your Experience Experience & Education: 8 years of post-academic industry experience developing and deploying machine learning models in production environments, with a Ph.D. or Master’s degree in Computer Science, AI, Applied Mathematics, or a related field. Deep Learning Expertise: Mastery of modern deep learning frameworks (PyTorch, JAX) and extensive hands-on experience with modern architectures (Transformers, LLMs). Generative AI & LLM Security: Proven experience with the modern LLM stack (pre-training, fine-tuning via LoRA/SFT, RAG) and a strong understanding of LLM security vulnerabilities, guardrails, and alignment techniques. Research-to-Product Track Record: Demonstrated history of successfully transitioning complex AI research or prototypes into high-throughput, low-latency production systems at scale. Engineering Proficiency: Advanced skills in Python and standard software engineering workflows, with experience deploying models using high-performance inference servers (vLLM, Triton, ONNX) and containerized orchestration (Docker, Kubernetes). Technical Communication: Exceptional ability to distill complex statistical and architectural concepts for non-technical stakeholders and partner effectively with cross-functional executive leadership. 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

Modern Engineering Best Practices: Evangelize and implement modern engineering best practices, including agentic coding workflows, reproducible research pipelines, and spec-driven development within the team.
Mentorship & Technical Excellence: Mentor senior and junior engineers and researchers, fostering a culture of technical excellence, algorithmic rigor, and continuous learning within the team.
Deep Learning Expertise: Mastery of modern deep learning frameworks (PyTorch, JAX) and extensive hands-on experience with modern architectures (Transformers, LLMs).
Generative AI & LLM Security: Proven experience with the modern LLM stack (pre-training, fine-tuning via LoRA/SFT, RAG) and a strong understanding of LLM security vulnerabilities, guardrails, and alignment techniques.
Research-to-Product Track Record: Demonstrated history of successfully transitioning complex AI research or prototypes into high-throughput, low-latency production systems at scale.
Technical Communication: Exceptional ability to distill complex statistical and architectural concepts for non-technical stakeholders and partner effectively with cross-functional executive leadership.
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

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlmachine learningllmpythondockerkubernetes

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Vision