AI Partnerships Solutions Architect

A core deliverable of this role is the continuous creation of architecture artifacts that make Prisma AIRS tangible and deployable for partners and their customers.

• Architecture Design: Design comprehensive architecture diagrams and detailed technical blueprints for secure AI deployments across cloud, data center, and hybrid environments.

• Prisma AIRS Insertion Points: Identify and document critical insertion points for the full Prisma AIRS portfolio AI Model Security, AI Red Teaming, AI Runtime Security, and AI Agent Security within partner-built AI solutions.

• Tech Stack Navigation: Navigate and map typical GSI AI tech stacks including LLMs, vector databases, orchestration frameworks (LangChain, LlamaIndex), MCP servers, and cloud-native AI services to design seamless AIRS integration patterns.

• Rapid Technology Mastery: Demonstrate an exceptional ability to learn new and emerging technologies quickly, translating nascent capabilities - such as new inference providers or evolving agentic frameworks - into actionable architecture patterns.

2. Joint Use Cases & Technical Value Propositions

Drive partner adoption by creating scalable, reusable technical assets that articulate the value of Prisma AIRS within the context of partner solutions.

• Use Case Development: Create compelling, scenario-based use cases that demonstrate how GSIs, consulting firms, and technology ISVs can integrate and embed Prisma AIRS into their managed services, platforms, and customer-facing solutions.

• Joint Value Propositions: Build joint technical value propositions with partners connecting partner AI capabilities to Prisma AIRS security outcomes covering prompt injection prevention, data leakage protection, AI agent security, and model vulnerability defense.

• ISV & Platform Integration: Engage technology ISV partners such as ServiceNow and NVIDIA ecosystem partners to identify and productize integration patterns that embed Prisma AIRS natively within their platforms.

• Partner Enablement: Deliver technical workshops, architecture reviews, and enablement sessions with GSI and consulting firm technical teams to build partner-side Prisma AIRS expertise at scale.

3. Joint Reference Architectures & Lighthouse Customers

Turn partner integrations into repeatable, customer-proven patterns that the broader ecosystem can adopt.

• Reference Architecture Development: Build joint reference architectures co-developed with GSI and ISV partners, grounded in real-world deployment patterns, that serve as the definitive blueprint for secure AI adoption using Prisma AIRS.

• Lighthouse Customer Engagement: Work directly with lighthouse customers alongside partner teams to validate reference architectures in production environments, creating case studies and proof points that accelerate broader market adoption.

• Customer Conviction: Articulate the technical and business value of Prisma AIRS to both deeply technical engineering teams and executive stakeholders at partner organizations and their end customers.

• Scalable Assets: Package validated architectures, POC scripts, and deployment guides into repeatable, self-service assets that partner technical teams can leverage independently.

4. Design & Build

This role requires the rare ability to both design and build translating complex AI security architectures into clear, compelling visual artifacts that GSI, Consulting, and ISV partners can immediately understand, present to their customers, and act upon. The ability to make the complex simple through great visual communication is as important as the technical depth behind it.

• Technical Architecture Diagrams: Design and produce detailed, publication-quality architecture diagrams that illustrate how Prisma AIRS integrates within partner AI solutions. Diagrams must be clear enough for a GSI architect to present directly to an enterprise customer without additional explanation.

• Lucidchart & Google Slides Proficiency: Expert-level use of Lucidchart for architecture diagrams and Google Slides for executive-ready technical presentations. Ability to build layered, visually clean diagrams that work equally well in a partner boardroom and a technical deep-dive.

• Visualizing Complex Architectures: Translate multi-layer AI system architectures spanning inference infrastructure, orchestration frameworks, data pipelines, and security controls into clear, logical visual flows that non-specialist audiences at GSI, Consulting, and ISV partners can grasp and champion internally.

• Partner-Ready Visual Assets: Build a library of reusable architecture templates, slide decks, and diagram components tailored to each partner type GSI delivery teams, consulting practice leads, and ISV platform architects so that Prisma AIRS integration patterns are easy to adopt, customize, and embed in partner proposals.

• Python Development: Write, review, and maintain Python scripts and integration code that demonstrate Prisma AIRS capabilities, automate security configurations, and power functional proof-of-concepts.

• AI Inferencing: Configure and test AI inference pipelines using platforms such as NVIDIA NIM, Together.ai, and major cloud inference services, integrating Prisma AIRS security controls at each layer.

• Proof-of-Concept Delivery: Build end-to-end technical POCs that demonstrate secure AI interactions, prompt injection detection, data loss prevention, and AI agent behavior monitoring and document them visually so partners can replicate and extend the work.

• API & Gateway Configuration: Configure AI gateways and integrate Prisma AIRS APIs within partner technology environments to validate real-world deployment scenarios.

5. Strategic Advisory & Field Intelligence

• Subject Matter Expertise: Act as the internal and external authority on AI security architectures, representing Palo Alto Networks in executive partner meetings, industry forums, and technical advisory sessions.

• Product Feedback Loop: Translate field observations from partner deployments and customer engagements into actionable feedback for Prisma AIRS product and engineering teams.

• Market Intelligence: Monitor emerging AI technologies, new inferencing platforms, and evolving agentic frameworks to ensure Prisma AIRS insertion strategies remain current and ahead of the market.

CRITICAL KNOWLEDGE AREAS

Prisma AIRS & Palo Alto Networks Platform Essential

• Prisma AIRS Portfolio: Deep knowledge of AI Model Security, AI Red Teaming, AI Runtime Security, and AI Agent Security their capabilities, deployment models, and API interfaces.

• Next-Generation Firewalls (NGFW): Architecture, deployment patterns, and integration in data center, cloud, and hybrid environments. Understanding of how firewalls enforce policy for AI workloads.

• CDSS (Cloud-Delivered Security Services): Familiarity with Threat Prevention, DNS Security, Advanced WildFire, and their applicability to protecting AI infrastructure and workloads.

• AI Gateway Configuration: Inline security enforcement for LLM traffic, prompt inspection, response filtering, and integration with AIRS runtime controls.

AI & Inferencing Technologies Essential

• NVIDIA: Hands-on knowledge of NIM microservices, NVIDIA AI Enterprise, and GPU-accelerated inference infrastructure and how to apply Prisma AIRS controls within these environments.

• Inference Platforms: Experience with Together.ai, Neoclouds, and major cloud inference services (AWS Bedrock, Azure OpenAI, GCP Vertex AI) including their API patterns and security considerations.

• LLM Architectures: Prompt engineering, RAG pipelines, vector databases, embedding models, and fine-tuning workflows understanding both capability and attack surface.

• Agentic Frameworks: LangChain, LlamaIndex, AutoGen, CrewAI, and Model Context Protocol (MCP) understanding agent-to-agent communication patterns and their security implications.

• Python Scripting: Proficiency in writing integration scripts, automation tooling, API wrappers, and technical demonstrations in Python.

Partner Ecosystem & Security Fundamentals Important

• GSI Technology Stacks: Deep familiarity with how Deloitte, Cognizant, NTT, Wipro, and similar firms architect and deliver AI solutions for enterprise clients.

• Identity & Access Management in AI Workflows: Securing agent identities, service accounts, API key lifecycle management, and least-privilege access within agentic AI systems.

• Cloud-Native AI Services: AWS, Azure, and GCP AI/ML services and their integration patterns with enterprise security controls.

• Experience: 8+ years in Solutions Architecture, Systems Engineering, or Technical Partner Management with a dedicated focus on AI/ML and/or cloud security architectures.

• GSI & Consulting Background: Proven experience working at or in close partnership with major GSIs (Deloitte, Cognizant, NTT) and top-tier management consulting firms (McKinsey, BCG), with an understanding of how they architect and sell AI solutions.

• AI Tech Stack Mastery: Deep, hands-on understanding of modern AI solution architectures including LLM integrations, AI gateways, RAG pipelines, agentic workflows, and vector databases.

• Prisma AIRS & Platform Knowledge: Ability to rapidly master the Prisma AIRS portfolio. Prior knowledge of Palo Alto Networks firewalls and CDSS is critical.

• Security Fundamentals: Strong understanding of data center security architectures including NGFW deployment, threat prevention, and securing AI workloads against prompt injection, insecure outputs, and model vulnerabilities.

• Agent & Identity Security: Understanding of how to secure AI agents, enforce least-privilege access, and manage identity within complex AI workflows.

• Technical Depth: Proficiency in Python scripting, API integrations, and inference platform configuration. Expert-level ability to create detailed architecture diagrams and executive presentations using Lucidchart, Google Slides, and equivalent tools.

• Communication Excellence: Exceptional ability to articulate complex technical value propositions to both deeply technical engineers and C-level executive stakeholders.

• Technology Passion: Deeply passionate about emerging AI architectures, new inferencing technologies, and driving innovation at the frontier of AI security.

PREFERRED QUALIFICATIONS

• Engineering Background: Strong software engineering or development background, enabling credibility and deep collaboration with partner technical teams.

• Education: Degree in Computer Science, Computer Engineering, or a related technical discipline.

• AI Security Hands-On Experience: Hands-on experience with AI model security, AI red teaming, and securing Model Context Protocol (MCP) interactions.

• ISV's like ServiceNow, Databricks, Glean

• NVIDIA Ecosystem: Technical knowledge of NVIDIA NIM, AI Enterprise, and GPU inference infrastructure.

• Inference Provider Knowledge: Experience with inference platforms such as Together.ai, Neoclouds, or equivalent providers.