Job Description

Your Career

As a Principal AI Engineer for the Enterprise AI Platform, you will be a pivotal technical leader driving the identification, design, and hands-on implementation of AI-powered solutions that directly address critical business challenges across IT and all enterprise functions (Sales, Marketing, Finance, HR, Legal, etc.). You will operate where AI innovation, top-tier engineering, and significant business outcomes converge, acting as the technical bridge between complex business problems and cutting-edge AI execution. Leveraging our robust Enterprise AI Platform, you will translate ambiguous problems into concrete AI solution designs, build core components of these solutions, and ensure their successful deployment and measurable impact, supporting both code-based and low-code/no-code approaches.

Your Impact

• Applied AI Solution Design & Architecture: Deeply understand complex business problems and strategic objectives across various enterprise functions. Break down ambiguous AI problems into concrete, actionable AI solution designs, including identifying the appropriate AI models, data requirements, and integration points for end-to-end AI applications.
• Hands-on Development & Implementation: Lead the hands-on development and implementation of key components of the AI assistant, agent, app, supporting both traditional and Generative AI model development, deployment, and real-time inference systems. Drive the successful integration of experimental AI technologies into production, showcasing tangible business value through rapid prototyping and measurable results.
• System Design & Optimization: Contribute significantly to the detailed design of large-scale, distributed AI/ML systems, ensuring performance, reliability, security, and developer-friendliness. Optimize existing systems for scalability, efficiency, and maintainability, ensuring the platform's ability to handle massive scale data and inference requests, optimizing for low latency and high throughput for real-time AI applications.
• Rapid Experimentation & Integration: Evaluate and integrate new AI tools, frameworks, SDKs, and cloud solutions into the platform, ensuring alignment with architectural strategy and engineering needs. Lead proof-of-concepts (POCs) for emerging AI innovations and drive their integration into production through long-term architectural evolution.
• Architectural Adherence & Best Practices: Champion and enforce design standards, patterns, and best practices for scalable and secure development of AI assistants, agents, and applications across various teams.
• Technical Leadership & Mentorship: Provide technical leadership and mentorship to other AI and ML engineers, fostering a culture of engineering excellence, innovation, and hands-on experimentation within the team and across the company.
• Cross-Functional Collaboration: Partner effectively with executive leadership, data science teams, engineering, product stakeholders, and business leaders to translate complex business use-cases into scalable, production-grade AI solutions. Act as a go-to expert for complex AI engineering challenges, providing technical guidance and hands-on support.
• Responsible AI & Governance: Implement features and practices that ensure AI systems comply with responsible AI principles, data governance, privacy laws, security policies, and ethical AI frameworks.
• Innovation & Research: Actively learn and incorporate advances in Agents, Generative AI, LLMs, and scalable AI architectures. Actively research and evaluate cutting-edge AI/ML techniques, algorithms, and models (e.g., foundation models, multi-modal AI) to identify opportunities for platform enhancement and new solution development.
• MLOps and Automation: Lead the implementation and continuous improvement of MLOps pipelines, including automated model training, versioning, deployment, and monitoring, to streamline the AI lifecycle. Design and implement automated testing strategies for AI models and platform components to ensure model quality, robustness, and drift detection.

Qualifications

Your Experience

• 10+ years of experience in software engineering, distributed systems, or enterprise architecture, including at least 5 years focused on leading AI/ML engineering or platform development.
• Proven expertise in designing and building complex, enterprise-grade AI/ML platforms and applications, ideally across multiple domains (e.g., customer support, finance, sales).
• Deep practical understanding of the full AI lifecycle for developing assistants, agents, and applications, including feature engineering, RAGs, model training, evaluation, validation, deployment, and monitoring.
• Extensive hands-on experience with distributed systems architecture, streaming data platforms, data lakes, and real-time decision engines.
• Generative AI & Large Language Models (LLMs): Direct hands-on experience with Generative AI technologies, including Large Language Models (LLMs), multi-modal models, RAGs (Retrieval-Augmented Generation), and agentic AI systems. Familiarity with techniques for LLM alignment, fine-tuning, and responsible deployment.
• Proficiency in modern AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX) and cloud AI/ML platforms (e.g., AWS SageMaker, Google Cloud AI Platform/Vertex AI, Azure ML).
• Strong programming skills in languages such as Python, Java, or Go.
• Excellent communication skills with a track record of influencing technical and cross-functional stakeholders at VP+ levels.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• System-Level Thinking: Demonstrated ability to think at a system level, understanding complex interdependencies within distributed AI architectures and optimizing end-to-end performance.

Preferred Qualifications

• Master's degree or Ph.D. in Computer Science, Machine Learning, or a related technical field.
• Experience contributing to open-source AI projects or publications in top-tier AI conferences.
• Prior experience in a technical consulting or solutions architecture role, bridging technical teams and senior business stakeholders.
• Deep understanding of cybersecurity principles as they apply to AI systems.

The Ideal Candidate: You are a systems thinker and AI evangelist with the ability to scale complex ideas into architecture that lasts. You thrive in ambiguity, excel at influencing across technical and business domains, and are driven to make AI core to the fabric of a company's digital transformation. You are a hands-on AI engineering leader with a passion for building robust, scalable AI platforms and the ability to translate strategic business needs into innovative, impactful AI solutions.

Additional Information

The Team

Working at a high-tech cybersecurity company within Information Technology is a once-in-a-lifetime opportunity. You’ll join the brightest minds in technology, creating, building, and supporting tools and enabling our global teams on the front line of defense against cyberattacks.

We’re connected by one mission but driven by the impact of that mission and what it means to protect our way of life in the digital age. Join a dynamic and fast-paced team of people who feel excited by the prospect of a challenge and feel a thrill at resolving technical gaps that inhibit productivity.

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/commissioned roles) is expected /YR. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here.

Our Commitment

We’re problem solvers that 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.