Global Solutions Architect – AI and Automation

This is a fully remote position, open to applicants in Texas.

📋 Description

• Take ownership of the Technical Services automation portfolio, comprising scripts, API integrations, configuration migration and validation tooling, and workflow orchestration.

• Design and manage production platforms for assessments of maturity and security across NGFW, Strata Cloud Manager, Prisma Access, Cloud-Delivered Security Services, and Prisma SD-WAN.

• Create assessment catalogs, parsers, and evaluators with measurable accuracy metrics.

• Design and implement multi-agent AI systems utilizing advanced models like Gemini and Claude on Vertex AI.

• Implement zero-trust principles, least-privilege access, workload segmentation, encryption, continuous verification, and telemetry.

• Conduct threat modeling and secure AI systems against prompt injection, excessive agency, sensitive data disclosure, insecure tool access, and RAG data leakage.

• Develop full-stack features using TypeScript, Python, and React, incorporating authorization, tenant isolation, credential encryption, and audit logging.

• Manage CI/CD pipelines and Terraform-managed infrastructure on GKE across multiple regions.

• Validate platform changes against live firewall, Prisma Access, and SD-WAN lab environments.

• Lead harness engineering initiatives, including agent harnesses, skills, MCP servers, sub-agent roles, hooks, context files, and quality gates.

• Leverage automation and AI for documentation, enablement content, service SKU development, and launch readiness.

• Translate Technical Services priorities into architecture, roadmaps, and delivered capabilities.

• Provide updates to senior leadership regarding progress, risks, automation ROI, adoption, engagement outcomes, and AI expenditure.

• Deliver tooling, enablement, and reference architectures to Customer Success and Professional Services teams.

• Publish guidance, present at internal forums, and influence the organization’s secure-AI perspective.

• Collaborate with Product, Engineering, Sales, Security, and IT teams.

• Contribute to open-source SDKs for Palo Alto Networks APIs.

• Mentor engineers, publish reference implementations, and hold regular office hours.

⛳️ Requirements

• 8–12 years of professional experience in software development.

• Proven experience in designing, shipping to production, and owning at least one full-stack system post-launch.

• Expertise in full-stack engineering, including frontend, backend APIs, relational data modeling and SQL, cloud infrastructure, containers, Kubernetes, infrastructure as code, and CI/CD.

• Proficient in TypeScript and Python.

• Experience making first-principles architectural decisions.

• Strong software design and testing discipline, including clear interfaces, separation of concerns, dependency injection, and automated testing in CI.

• Solid foundation in cybersecurity, including OWASP Top 10, secure coding practices, threat modeling, OAuth 2.0, OIDC, mTLS, RBAC, secrets and key management, and secure software supply chains.

• Ability to apply NIST SP 800-207 and CISA Zero Trust Maturity Model principles.

• Knowledge in network and security engineering, including routing, segmentation, policy, VPN, SASE, and threat prevention.

• Hands-on experience with LLMs, agents, skills, MCP, and coding agents.

• Advanced knowledge in harness engineering, including context and memory management, tool and skill design, guardrails, permissions, verification loops, evaluation, and cost/token control.

• Traditional automation experience with REST and XML APIs, Python, Bash, configuration-as-code, infrastructure as code, and workflow orchestration.

• Familiarity with advanced AI concepts such as context windows, tool calling, structured outputs, RAG, embeddings, evaluation, hallucination, and non-determinism.

• Production experience in building and operating an LLM-backed application with tool-using agents.

• Knowledge of OWASP Top 10 for LLM Applications and Agentic Applications, MITRE ATLAS, and NIST AI Risk Management Framework.

• Experience with prompt-injection controls, excessive-agency controls, sensitive-data protection, MCP security, RAG permission boundaries, and AI supply-chain risk management.

• Production experience on a major cloud platform, preferably Google Cloud, with infrastructure as code using Terraform or OpenTofu.

• Strong communication skills to engage with executives and produce design documents and status reports.

• Proven track record of cross-functional influence across business units and teams.

• Comfortable working asynchronously with global teams across different time zones.

• Bachelor's degree in Computer Science, Software Engineering, Electrical or Computer Engineering, or a related technical field.

• Preferred qualifications include experience with PAN-OS, Panorama, Strata Cloud Manager, Prisma Access, PCNSE, AI security platforms, AI red teaming, network automation, Google ADK, Claude Agent SDK, MCP servers, professional-services documentation, Bun, Hono, Zod, Drizzle, Vite, Cortex, multi-region architecture, data residency, cloud FinOps, CISSP, CCSP, OSCP, open-source maintenance, or leading engineering practices.

🏝️ Benefits

• Restricted stock units.

• Bonus opportunities.

• Reasonable accommodations for qualified individuals with disabilities or special needs.

• Immigration sponsorship is not available.