Global Solutions Architect - AI and Automation

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!

This role is remote, but distance is no barrier to impact. Our hybrid teams collaborate across geographies to solve big problems, stay close to our customers, and grow together. You will be part of a culture that values trust, accountability, and shared success where your work truly matters.

Job Summary

The Technical Services Center of Excellence (CoE) builds the platforms, tooling and AI capabilities our engineers use to deliver security outcomes for customers. As Global Solutions Architect for AI Network Security, you will own the automation strategy for network security delivery. That spans traditional automation (scripting, API integrations, configuration management and workflow orchestration) as well as AI, which now plays a central role in the work. That includes assessing deployments, prescribing improvements, automating migrations, and providing conversational and agentic tools to consultants worldwide.

This is a full-stack role in the broadest sense. You are expected to be deeply fluent across the entire stack: frontend, backend, data, cloud infrastructure, CI/CD, networking and cybersecurity. You also need to understand how modern AI systems work and how they fail. You design zero trust into everything you build, you understand the threat landscape for LLMs and autonomous agents, and you know the controls that address it. You reason from first principles, ship to production, and raise the engineering standard of the people around you.

The role sits where business leadership, thought leadership and technical depth meet. You turn leadership priorities into technical direction, shape how the organization thinks about AI and security, and deliver working capabilities to our field teams in Customer Success and Professional Services. You report regularly to senior leadership within Technical Services, and you build the relationships across business units that let Technical Services execute more efficiently.

Your Impact

- Own the Technical Services automation portfolio end to end: scripts, API integrations against PAN-OS, Strata Cloud Manager and Prisma APIs, configuration migration and validation tooling, and workflow orchestration. Choose deterministic automation or AI based on what the problem needs.
- Architect and own production platforms that run maturity and security assessments across NGFW, Strata Cloud Manager, Prisma Access, Cloud-Delivered Security Services and Prisma SD-WAN.
- Design assessment catalogs, parsers and evaluators with measurable accuracy: parser coverage, license-entitlement gating, and readiness reported as measured rather than rounded up.
- Design and operate multi-agent AI systems on frontier models (for example Gemini and Claude on Vertex AI), including tool design, agent loops, structured outputs, retrieval, refusal handling and output-quality evaluation.
- Apply zero trust principles end to end: identity-based, per-request access for users, services and AI agents; least-privilege, short-lived credentials; segmented workloads; encryption in transit and at rest; continuous verification and telemetry.
- Secure AI systems by design. Threat-model agents and LLM features, defend against direct and indirect prompt injection, constrain agent autonomy and tool permissions, protect sensitive data in prompts, context and retrieval, and add guardrails and human approval where actions carry risk.
- Build full-stack features in TypeScript, Python and React, with authorization, tenant isolation (row-level security), credential encryption and audit logging designed in from the start.
- Operate CI/CD pipelines and Terraform-managed infrastructure on GKE across multiple regions, owning supply-chain controls, data residency, rollout safety, observability and incident follow-through.
- Validate platform changes against live firewall, Prisma Access and SD-WAN lab environments before release.
- Lead harness engineering for the Center of Excellence. Design and maintain the agent harnesses, skills, MCP servers, sub-agent roles, hooks, context files and quality gates that let engineers use coding agents (Claude Code or similar) safely and productively.
- Make the Center of Excellence measurably more productive across its release schedule. Apply automation and AI to documentation, enablement content, service SKU development and launch readiness, so that new services and releases ship on time with complete supporting material.
- Act as the bridge between business leadership and engineering: translate Technical Services priorities into architecture, roadmaps and delivered capabilities, and explain technical trade-offs in business terms.
- Provide regular updates to senior leadership within Technical Services on progress, risks, automation ROI (hours saved, adoption, engagement outcomes) and AI spend.
- Deliver tooling, enablement and reference architectures to field teams in Customer Success and Professional Services, and use their feedback to shape what gets built next.
- Act as a thought leader on AI and network security: publish guidance, present at internal forums, and shape the practice's point of view on secure AI adoption.
- Collaborate across business units, including Product, Engineering, Sales, Security and IT, and build relationships that remove friction and help Technical Services execute more efficiently.
- Contribute to open-source SDKs for Palo Alto Networks APIs.
- Mentor engineers, publish reference implementations, and hold regular office hours.

Qualifications

Required

- 8-12 years of professional software development experience. This includes at least one full-stack system you designed, shipped to production, and continued to own after launch.
- Expert full-stack engineering across every layer: modern frontend frameworks (React or similar), backend APIs and services, relational data modeling and SQL, cloud infrastructure, containers and Kubernetes, infrastructure as code, and CI/CD. Working proficiency in TypeScript and Python.
- Applied first-principles design: you can show a past architecture decision where you named the underlying constraint, chose what not to build, and justified the result.
- Software design and testing discipline: clear interfaces, separation of concerns, dependency injection, and automated tests enforced in CI.
- Strong cybersecurity foundation: application security (OWASP Top 10, secure coding, threat modeling), identity and access management (OAuth 2.0, OIDC, mTLS, RBAC), secrets and key management, and secure software supply chain practices (dependency pinning, SBOMs, provenance).
- Zero trust architecture: you can explain and apply NIST SP 800-207 principles and the CISA Zero Trust Maturity Model pillars (identity, devices, networks, applications and workloads, data) to a real system you built or secured.
- Network and security engineering: routing, segmentation, policy, VPN, SASE and threat prevention. You can deploy and test against a firewall, SASE or SD-WAN environment.
- Early and advanced adopter of generative AI: you have worked hands-on with LLMs, agents, skills, MCP and coding agents since they emerged, and you can show how your practice evolved with them. You use Claude Code or a similar agent harness at an advanced level every day, including multi-agent workflows, custom skills, hooks, sub-agents and MCP integrations.
- Harness engineering: a deep understanding of how to engineer the environment around a model. That covers context and memory management, tool and skill design, guardrails and permissions, verification loops, evaluation, and cost and token control. You can explain the design choices in a harness you built or customized.
- Traditional automation depth: REST and XML APIs, scripting (Python, Bash), configuration-as-code, infrastructure as code, and workflow orchestration. You know when a deterministic script beats an AI agent, and you can explain why.
- Advanced AI concepts: how LLMs behave, including context windows, tool calling, structured outputs, retrieval-augmented generation, embeddings, evaluation, and model limitations such as hallucination and non-determinism. You have built and operated at least one LLM-backed application with tool-using agents in production: you designed the tools, implemented the agent loop, and evaluated output quality.
- Security for AI systems: working knowledge of the OWASP Top 10 for LLM Applications and for Agentic Applications, MITRE ATLAS, and the NIST AI Risk Management Framework. You can describe controls you have implemented for prompt injection, excessive agency, sensitive data disclosure, insecure tool or MCP server access, RAG data leakage across permission boundaries, and AI model and supply chain risk.
- Production experience on a major cloud (Google Cloud preferred: GKE, Cloud SQL, IAM, Secret Manager or KMS) and infrastructure as code (Terraform or OpenTofu).
- Executive communication: you can present to senior leadership regularly, frame technical work in terms of business outcomes, and produce design documents and status reports that name risks, a critical path and a delivery forecast.
- Cross-functional influence: a track record of building relationships and driving outcomes across business units and teams you do not manage, including with field teams such as Customer Success and Professional Services.
- Comfortable working asynchronously with global teams across time zones.
- Bachelor's degree in Computer Science, Software Engineering, Electrical or Computer Engineering, or a related technical field.

Preferred

- Hands-on experience with PAN-OS, Panorama, Strata Cloud Manager or Prisma Access, or a certification such as PCNSE.
- Experience integrating AI security platforms such as Prisma AI Runtime Security (AIRS), or AI guardrail and red-teaming tooling.
- Familiarity with Google SAIF, ISO/IEC 42001, or the NIST AI 600-1 Generative AI Profile.
- Experience with AI red teaming, LLM evaluation pipelines, or AI observability and tracing.
- Experience with network automation tooling such as Ansible, Terraform providers for network devices, or pan-os-python and similar SDKs.
- Experience with Google ADK, Claude Agent SDK, or authoring and publishing MCP servers, skills or plugins for others to use.
- Experience producing technical documentation, enablement programs or service offerings (SKUs) in a professional services or customer success organization.
- Experience with Bun, Hono, Zod, Drizzle or Vite.
- Experience with Cortex or Cloud-Delivered Security Services.
- Experience with multi-region architecture, data residency or cloud FinOps.
- Security certifications such as CISSP, CCSP or OSCP.
- Open-source maintainership or public SDK contributions.
- Experience leading a small engineering team or practice, including onboarding and enablement.
- Technology You Will Work With
- Palo Alto Networks: PAN-OS and Panorama, Strata Cloud Manager, Prisma Access, Prisma SD-WAN, Advanced Threat Prevention, DNS Security, Advanced URL Filtering, WildFire, Enterprise DLP, Prisma AIRS, Cortex, Insights APIs.
- AI: Gemini and Claude on Vertex AI, Google ADK, MCP, agent skills and plugins, an AI gateway.
- Stack and platform: TypeScript on Bun, Python, React, Hono, Drizzle, Zod, Postgres, Redis, OpenAPI, GKE in EU and US regions, Terraform, GitLab CI, Okta OIDC.

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 .

$175,200.00 - $240,900.00/yr

Our 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.