Staff/Sr. Staff AI Engineer - Enterprise AI Solutions

Palo Alto Networks•Office - USA - CA - Headquarters, CA

1d•$163,200 - $264,000•Onsite

About The Position

As a Staff/Sr. Staff AI Engineer for Enterprise AI Solutions, you will be a technical leader responsible for the hands-on design, development, and implementation of AI-powered solutions for challenging business problems across IT and enterprise functions such as Sales, Marketing, Finance, HR, and Legal. You will work with Principal and Distinguished Architects to translate high-level strategies into concrete designs and robust, scalable, and ethical implementations. The role requires deep technical expertise, complex problem-solving, and mentoring engineers while using the Enterprise AI Platform to deliver measurable business impact. You will lead AI solution design and implementation, contribute to enterprise AI/ML platform components, and develop traditional and generative AI model deployment and real-time inference systems. You will optimize large-scale systems for performance, reliability, low latency, high throughput, and developer-friendliness; evaluate emerging tools and cloud solutions; and champion architectural standards. You will mentor engineers, collaborate across functions, enforce responsible AI and security practices, implement testing and monitoring, and apply current AI/ML techniques and research. Palo Alto Networks states that most teams work from the office full time, with flexibility when needed, to support in-person collaboration. Compensation is listed as $163,200–$264,000 per year, depending on qualifications, experience, and work location. Compensation may also include restricted stock units and a bonus. Immigration sponsorship is not available for this position.

Requirements

At least 8 years of software engineering experience, including at least 5 years of Data Science/AI/ML experience.
Experience deploying enterprise AI/ML systems.
Understanding of the AI lifecycle.
Experience with distributed systems and streaming data.
Hands-on experience with Generative AI and LLMs.
Proficiency in AI/ML frameworks and cloud platforms.
Strong programming skills in Python and C++.
Excellent communication skills.
Bachelor’s or master’s degree in Computer Science or a related field.
Strong foundation in machine learning theory and application, deep learning, and statistical modeling.
Strong analytical and critical-thinking skills for complex, ambiguous problems.
Ability to design, build, and deploy scalable, robust AI systems, with understanding of MLOps and data engineering principles.
Ability to communicate technical concepts to technical and non-technical audiences and collaborate across functions.
Understanding of how AI can drive business value and translate technical work into tangible outcomes.
Passion for keeping up with advancements in AI.

Nice To Haves

PhD in Computer Science, Applied Mathematics, Machine Learning, or a related computational field.
Experience with open-source AI projects.
Prior technical lead role for AI/ML projects.
Familiarity with cybersecurity principles for AI.
Track record of conceiving and executing novel research, publishing in top-tier conferences or journals, or delivering innovative AI solutions with significant business impact.
Experience leading projects, guiding junior team members, and influencing technical direction.
Experience with Python, R, TensorFlow, PyTorch, and scikit-learn.

Responsibilities

Lead the design and implementation of AI solutions, translating business problems into AI designs and managing model selection, data requirements, and integrations.
Develop and implement core components of the enterprise AI/ML platform, ensuring scalability and security.
Contribute to the lifecycle of traditional and generative AI model deployment and real-time inference systems.
Design and optimize large-scale AI/ML systems for performance, reliability, and developer-friendliness, including low latency and high throughput for real-time applications.
Evaluate and integrate AI tools, frameworks, and cloud solutions in line with architectural guidelines, and lead proofs of concept for emerging AI innovations.
Champion AI system design standards and best practices, guiding junior engineers.
Mentor AI/ML engineers, lead design discussions, and perform code reviews.
Partner with Data Scientists, ML Engineers, Product Managers, and IT stakeholders to develop production-grade AI solutions.
Ensure AI systems comply with responsible AI principles and security policies; implement automated testing and monitoring.
Apply current AI/ML techniques to solve problems and improve solutions, keeping up with developments in generative AI and LLMs.