Platform Architect/ Engineer (Platform & Cloud)

Company Description

PaiDevo is transforming corporate learning with AI-driven personalization that adapts to each learner’s cognitive profile. Our platform turns generic training into measurable performance outcomes — improving engagement, accelerating skill acquisition, and increasing workforce productivity. Powered by proprietary cognitive intelligence and an API-first architecture, PaiDevo enables enterprises to deliver personalized learning at scale.

Role Description

Part-time · Equity-Based

As a Platform Architecture Advisor, you will guide the design of PaiDevo’s cloud and platform architecture to support our Adaptive Learning Intelligence platform. You will help define scalable infrastructure patterns, security foundations, and system integration standards, ensuring the platform is enterprise-ready.

You will work closely with the founding team and AI architects to review architectural decisions, advise on best practices, and support the transition from prototype to production — without being responsible for day-to-day implementation.

• Design and build cloud infrastructure on GCP (networking, IAM, VPC, compute, storage)
• Lead backend platform architecture (APIs, authentication, multi-tenant systems)
• Build secure, scalable production environments (CI/CD, monitoring, logging)
• Own security and compliance foundations (data isolation, access control, enterprise security standards)
• Design data pipelines to support AI and cognitive profiling systems
• Enable enterprise deployment options (private cloud, on-prem readiness)
• Collaborate with AI engineers to operationalize ML pipelines
• Make architecture decisions for performance, cost efficiency, and reliability

• Strong experience in cloud infrastructure (GCP preferred)
• Backend engineering experience (Python / Node / Go or similar)
• Experience with containerization and orchestration (Docker, Kubernetes)
• Knowledge of security best practices (IAM, networking, data privacy)
• Experience building scalable SaaS or enterprise platforms
• Startup mindset — hands-on, ownership-driven, comfortable with ambiguity

• Experience with AI/ML infrastructure pipelines
• Enterprise SaaS or regulated environments
• DevOps / SRE background
• Experience with SOC2 / ISO readiness