Principal Architect – AI-Native Security Platform

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OpenVPN Inc.

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2002

🔒 Cybersecurity

☁️ SaaS

📡 Telecommunications

💰 Equity Crowdfunding on 2013-10

Cybersecurity • SaaS • Telecommunications

OpenVPN Inc. is a company that provides secure and flexible VPN solutions for remote access and network security. It offers both cloud-delivered and self-hosted solutions featuring private access, secure web access, and SaaS protection, allowing businesses to protect their hybrid workforce. OpenVPN's services support zero trust access and help reduce the attack surface by implementing security protocols like role-based access control and device identity checks. The company is trusted by nearly 20,000 customers worldwide, supports major cloud providers, and offers an easy-to-use and scalable solution for secure networking.

📋 Description

• Own architectural coherence and technical direction across CipherScale’s AI-native platform • Define and evolve the boundary between AI reasoning, the MCP capability layer, the CipherScale Controller, and customer infrastructure • Define how AI agents securely discover, reason about, and invoke CipherScale capabilities • Establish separation between probabilistic AI reasoning and deterministic security-sensitive execution • Design for CipherScale AI Admin, external AI clients, enterprise integrations, and future machine-to-machine interactions • Own MCP strategy covering tools, resources, apps/UI, long-running tasks, human-in-the-loop interactions, discovery, authentication, authorization, schemas, and extensions • Track MCP specifications, SEPs, SDKs, security guidance, and ecosystem changes, translating changes into architecture decisions • Design Zero Trust and least-privilege security architecture, identity, authorization, credential isolation, secrets management, auditability, and policy enforcement • Design distributed systems and cloud architectures including control/data-plane separation, SaaS and self-hosted enterprise architectures, multi-tenancy, Kubernetes, cloud platforms, asynchronous workflows, gateways, high availability, observability, and failure recovery • Understand current architecture, identify key risks, review AI/MCP implementation, establish architectural invariants, strengthen ADR processes, define MCP capability architecture, and document trust boundaries • Validate architecture through working implementations of representative AI-native workflows, including a complex multi-step infrastructure operation • Collaborate directly with technical leadership and product engineers • Prototype and turn architecture into implementable systems

🎯 Requirements

• Deep experience building complex distributed platforms, security products, cloud infrastructure, networking systems, developer platforms, or similarly demanding systems • Evidence of personally designing systems that survived real-world scale, security threats, organizational complexity, and changing requirements • Strength in distributed systems and cloud architecture • Security architecture and Zero Trust expertise • Identity and authorization expertise • API and protocol design • Agentic AI systems and MCP or comparable agent/tool protocols • SaaS and multi-tenant architecture • Kubernetes and cloud-native systems • Networking, event-driven systems, observability, and key management • Strong software engineering skills and ability to prototype • Ability to read specifications, follow emerging standards, prototype quickly, and recognize architectural shifts • Systems thinking about trust boundaries, failure modes, data flows, state, scaling, and operability • Security mindset focused on system failure and abuse • Product judgment regarding architecture, speed, trust, customer value, and differentiation • Hands-on implementation responsibility and practical implementation instincts

🏖️ Benefits

• Competitive pay rates • Fully remote work environments • Self-managed time off • Competitive salary and comprehensive benefits • A senior ownership role with responsibility for a critical engineering surface • The autonomy to define platform strategy, standards, and technical direction • The opportunity to build foundational systems with immediate, measurable impact • A fast-moving, AI-native engineering environment • Direct collaboration with technical leadership and product engineers • Support to experiment, automate, and introduce better ways of working • A culture that values speed, ownership, sound judgement, and reliable delivery