We are looking for a Senior Software Engineer (Backend) to help build out the next generation of the Planstin Membership Platform—a complex system that spans membership management, pricing engines, CRM integrations, ETL pipelines, and an evolving AWS-based microservice architecture. In this role, you’ll work directly with the founder/architect who built the current system, take ownership, anticipate problems before they surface, and propose thoughtful solutions. The right engineer must be comfortable adapting their plan when the business direction shifts. This is not a narrow feature-factory role. We need someone who can see the whole system, understand how the parts interact, and help push the architecture forward. This position is based in St. George Utah but we'll consider full time remote and out of state for the right candidate. What you'll do Backend (Primary) A large Nest.js backend powering: Distributed services deployed with AWS CDK (Lambda, RDS, S3, EventBridge, ECS/Fargate, etc.) A large Nest.js backend powering: Distributed services deployed with AWS CDK (Lambda, RDS, S3, EventBridge, ECS/Fargate, etc.) Frontend React SPA for internal and external membership tools Admin dashboards, configuration UIs, step-based workflows, and data visualization Integration with partner systems React SPA for internal and external membership tools Admin dashboards, configuration UIs, step-based workflows, and data visualization Integration with partner systems DevOps / Infrastructure AWS CDK (TypeScript) for infrastructure automation CI/CD optimization Observability, error handling, and performance tuning AWS CDK (TypeScript) for infrastructure automation CI/CD optimization Observability, error handling, and performance tuning Data & Domain Work Implementing and refining a high-complexity relational schema Helping convert messy real-world data into stable, normalized structures Identifying inconsistencies in business rules — and proposing solutions Implementing and refining a high-complexity relational schema Helping convert messy real-world data into stable, normalized structures Identifying inconsistencies in business rules — and proposing solutions Additional tasks will include Spot architectural risks early Suggest simplifications and abstractions Build tooling when manual work becomes repetitive Improve reliability of pipelines ingesting external data Question things that “don’t smell right” Understand the why behind every model, process, or mapping Ask great questions Provide options, not just code Spot architectural risks early Suggest simplifications and abstractions Build tooling when manual work becomes repetitive Improve reliability of pipelines ingesting external data Question things that “don’t smell right” Understand the why behind every model, process, or mapping Ask great questions Provide options, not just code