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About This Role
Santa Clara, California, United States Product Engineering Ref ID: JR\-016596
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
### The Team
Network Security (NetSec) Engineering – Our team is at the core of Palo Alto Networks' mission, developing the industry’s most advanced security platforms. We are now expanding our focus to build a suite of internal and customer\-facing AI\-enabled solutions designed to automate a variety of operations, and revolutionize how our teams interact with complex data. You will lead a specialized group of software engineers dedicated to integrating Generative AI and automation into the very DNA of our NetSec product portfolio and beyond.
### Job Summary
As the Director of Software Engineering for AI\-Enabled Solutions and Products, you will lead the development of a diverse portfolio of AI\-driven solutions that enhance our Network Security capabilities. You will be responsible for bridging the gap between core security engineering and cutting\-edge AI application, creating solutions that solve complex operational challenges. This role requires a leader who is equally comfortable discussing large\-scale software architecture and the nuances of LLM integration, while scaling high\-performing teams in a fast\-paced environment.
### Your Impact
- Define and execute the roadmap for AI\-enabled solutions within the NetSec organization, focusing on high\-impact areas across various business processes
- Drive the architectural direction for scalable, cloud\-native applications that leverage AI/ML to solve real\-world security problems.
- Partner with NetSec product leaders, AI Research teams, and Cloud Operations to ensure AI solutions are seamlessly integrated and production\-ready.
- Build and mentor a multi\-disciplinary engineering organization. You will be responsible for recruiting and developing top\-tier talent and managers focused on the intersection of SWE and AI.
- Identify opportunities to export successful AI solutions methodologies from NetSec to other organizations within Palo Alto Networks, driving a company\-wide "AI\-first" mindset.
- Oversee the full software development lifecycle (SDLC), ensuring high\-quality, secure, and performant code delivery in a continuous integration environment.
Qualifications
### Required Qualifications
- 12\+ years of software development experience, with a proven track record of shipping large\-scale, enterprise\-grade cloud services or internal product platforms.
- 6\+ years of formal engineering management experience, including experience managing other managers and leading geographically distributed teams.
- Deep hands\-on experience in modern software languages (e.g., Python, Golang, Java) and cloud\-native infrastructure (AWS/GCP, Kubernetes, Microservices).
- Recent experience delivering software products that utilize AI/ML, specifically involving LLM orchestration, AI Agents, RAG (Retrieval\-Augmented Generation), or AI\-driven automation workflows.
- Exceptional ability to articulate complex technical strategies to executive leadership and influence stakeholders across different business units.
### Preferred Qualifications
- Deep experience in network security, threat detection, or cloud\-based security solutions.
- Familiarity with AI development frameworks (e.g., LangChain, LlamaIndex) and MLOps best practices for deploying and monitoring AI applications at scale.
- BS/MS in Computer Science, Engineering, or a related technical field.
- Proven track record of taking a "vague" problem statement and turning it into a successful, AI\-enabled software product.
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.
$250,000\.00 \- $344,500\.00/yrOur 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 [email protected].
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.
Salary Context
This $250K-$344K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $190K across 193 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 3,824 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Palo Alto Networks, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $234,620 based on 682 positions with disclosed compensation. Director-level AI roles across all categories have a median of $243,000. This role's midpoint ($297K) sits 27% above the category median. Disclosed range: $250K to $344K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
Palo Alto Networks AI Hiring
Palo Alto Networks has 8 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, Data Scientist, AI Product Manager. Positions span Austin, TX, US, Santa Clara, CA, US, Charlotte, NC, US. Compensation range: $201K - $344K.
Location Context
Across all AI roles, 16% (613 positions) offer remote work, while 3,187 require on-site attendance. Top AI hiring metros: New York (2,448 roles, $210,000 median); San Francisco (1,990 roles, $253,000 median); Los Angeles (1,686 roles, $189,000 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (119) are outnumbered by mid-level (1,813) and senior (1,472) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,000. Top-quartile roles start at $253,000, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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