Web Development Engineer, Palo Alto Networks

• Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related technical discipline
• Approximately 10+ years of experience in software engineering, application development, AI engineering, or related technical roles, with hands-on AI application development experience
• Strong proficiency in Python and experience building production-grade applications, services, and integrations
• Experience working with LLMs, Generative AI APIs, prompt engineering, embeddings, vector search, and RAG architectures
• Strong understanding of REST APIs, distributed systems, application architecture, data processing, and software engineering best practices
• Experience with JavaScript or TypeScript and modern web technologies such as React, Next.js, Node.js, or comparable frameworks
• Familiarity with web development workflows, CMS platforms, content publishing operations, and digital experience ecosystems
• Experience with Git, automated testing, CI/CD pipelines, containerization, and cloud-based application deployment
• Understanding of application security, data privacy, responsible AI, and production software quality standards
• Strong analytical, problem-solving, communication, and cross-functional collaboration skills
• Technical Skills:
• AI & Machine Learning
• Generative AI, LLMs, prompt engineering, embeddings, RAG, AI agents, model evaluation, and guardrails
• Programming & Web Engineering
• Python, JavaScript/TypeScript, React or equivalent frameworks, Node.js, REST APIs, HTML5, and CSS3
• AI Infrastructure & Data
• Vector databases, document processing, API integration, structured data, retrieval pipelines, and enterprise knowledge systems
• Cloud & DevOps
• AWS, Azure, or GCP; Docker; Git; CI/CD; automated testing; monitoring; and deployment automation
• Digital Experience & Marketing Technology
• CMS platforms, web production workflows, personalization, SEO, digital analytics, experimentation, and content lifecycle management
• Quality, Security & Governance
• AI evaluation, accessibility validation, secure coding, data privacy, content governance, and production observability

Desirable

• We are seeking an experienced Web Development Engineer to drive automation into our Digital Experience Marketing organization, with a primary focus on web development, web production, and digital experience optimization
• Based in Santa Clara, this role will partner closely with web developers, digital marketers, UX/UI designers, content strategists, web producers, SEO specialists, and enterprise technology teams to design, develop, and deploy AI-powered solutions that improve website development efficiency, accelerate content production, enhance digital experiences, and optimize marketing performance
• The ideal candidate combines strong software engineering fundamentals with hands-on expertise in Generative AI, Large Language Models (LLMs), AI agents, retrieval-augmented generation (RAG), and automation frameworks
• They will translate business challenges in digital marketing and web operations into scalable, secure, and production-ready AI solutions
• This role will help transform Digital Experience Marketing from predominantly manual, execution-heavy web operations toward a more intelligent, automated, and data-driven operating model
• By embedding AI into web development, content operations,, and digital experience optimization, the AI Engineer will help improve delivery speed, operational scalability, digital quality, and the overall effectiveness of enterprise marketing experiences
• AI-Powered Web Development:
• Design and implement AI-powered tools that accelerate front-end and back-end web development, component creation, code generation, refactoring, and documentation
• Integrate LLM-based coding assistants and agentic workflows into existing development environments and software development lifecycle (SDLC) processes
• Develop reusable AI capabilities for generating web components, page templates, design system implementations, and code aligned with enterprise standards
• Build AI-driven solutions to assist with code reviews, debugging, test generation, accessibility compliance, and performance optimization
• Collaborate with engineering teams to integrate AI into modern web architectures, APIs, content management systems (CMS), and marketing technology platforms
• Establish guardrails to ensure AI-generated code meets standards for security, maintainability, scalability, and brand consistency
• Intelligent Web Production and Content Operations:
• Build AI-driven automation solutions to streamline end-to-end web production, including page creation, content ingestion, metadata generation, asset management, localization, and publishing workflows
• Develop AI assistants that support web producers in creating, updating, validating, and maintaining website pages at scale
• Integrate AI capabilities with enterprise CMS and digital experience platforms to reduce repetitive manual tasks and accelerate time to publish
• Implement automated validation for broken links, missing metadata, content inconsistencies, image alt text, page structure, and publishing readiness
• Use Generative AI to assist with content transformation, content tagging, taxonomy mapping, structured content generation, and content reuse across digital channels
• Introduce human-in-the-loop review and approval workflows for AI-generated content and production changes
• Generative AI, LLMs, and AI Agent Development:
• Design, develop, and deploy AI applications using commercial and open-source LLMs
• Build RAG-based solutions that retrieve relevant information from approved enterprise knowledge bases, content repositories, brand guidelines, web documentation, and technical standards
• Develop AI agents and multi-step workflows to automate complex web development and digital production tasks
• Apply prompt engineering, context management, structured outputs, tool calling, and model evaluation techniques to improve the reliability of AI applications
• Integrate AI services through REST APIs, SDKs, and enterprise integration frameworks
• Evaluate models and frameworks based on quality, latency, cost, security, and suitability for enterprise digital marketing use cases
• Digital Experience Optimization and Marketing Intelligence:
• Develop AI-powered capabilities for website personalization, content recommendations, audience segmentation, and contextual digital experiences
• Leverage website analytics, customer journey data, and campaign performance insights to identify opportunities for AI-driven optimization
• Support experimentation and conversion rate optimization through AI-assisted hypothesis generation, content variant creation, and analysis of A/B testing results
• Build intelligent solutions for SEO and content discoverability, including metadata recommendations, structured data validation, and content quality analysis
• Collaborate with analytics and marketing technology teams to integrate AI insights into existing reporting, experimentation, and optimization workflows
• Apply responsible data practices and consent requirements when working with customer or behavioral data
• Engineering Excellence and Production Readiness:
• Design scalable, maintainable, and observable AI applications and services suitable for enterprise deployment
• Implement CI/CD integrations, automated testing, version control, deployment pipelines, and release management practices for AI-powered solutions
• Apply MLOps and LLMOps principles, including model evaluation, prompt versioning, monitoring, tracing, and lifecycle management
• Optimize AI workloads for response time, throughput, reliability, and cost efficiency
• Document architectures, APIs, technical decisions, operational procedures, and reusable implementation patterns
• Partner with platform engineering, cybersecurity, legal, privacy, and IT teams to ensure production readiness and responsible AI adoption
• Cross-Functional Collaboration and Innovation:
• Work with Digital Experience Marketing leadership to identify high-value AI use cases across web development and web production operations
• Translate business requirements into technical solutions, prototypes, proof-of-concepts, and production implementations
• Partner with UX, content, SEO, analytics, marketing operations, and web platform teams to ensure solutions address real operational needs
• Establish reusable AI capabilities, engineering standards, reference architectures, and best practices across digital experience teams
• Document architecture, reusable patterns, implementation guidelines, and best practices for AI adoption
• Stay current with emerging AI engineering techniques, agentic workflows, web automation tools, and digital experience technologies
• Champion responsible AI practices, including human oversight, data privacy, security, explainability, and governance