100% Remote! Compensation $150K–$170K + 10% bonus and full-time benefits Senior Full Stack Backend Engineer We're building the operating system for live event ticketing at scale. The Independence platform is a TypeScript/Node.js API powering millions of transactions across high-stakes real-time POS workflows. We move fast ship reliably and hold our code to a high standard. We're looking for a Senior Full Stack Backend Engineer who uses AI as a force multiplier not a crutch. You deeply understand what you're building can explain every line you ship and hold yourself and your teammates to rigorous engineering standards. Tech Stack Core TypeScript · Node.js · Express · PostgreSQL · TypeORM · Redis · BullMQ · Tsyringe · Zod · OpenSearch · Docker · Kubernetes · AWS (S3 SNS SQS Lambda Secrets Manager) · Auth0 · Jest What You'll Work On Design and build backend services within a Domain-Driven Design architecture (Express TypeORM BullMQ Tsyringe Zod) from domain entities to HTTP handlers to async workers. Own complete features end-to-end schema design migrations API contract business logic serialization test coverage and observability. Build and iterate on AI-assisted tooling that meaningfully accelerates the team including prompt pipelines code generation workflows and AI-powered data processing — while maintaining full engineering ownership of what ships. Contribute to distributed systems concerns event outbox reliability queue worker durability (BullMQ/Redis) OpenSearch indexing and AWS-native integrations (S3 SNS SQS Lambda). Contribute to responsible AI adoption defining patterns for where AI tooling belongs in the stack how to validate its output and where human judgment is non-negotiable. Participate in technical design code review and on-call raising the bar for the team around you. What We're Looking For Backend Engineering Depth 5+ years with Node.js and TypeScript in production environments Strong fundamentals in relational database design (PostgreSQL) indexing constraints migrations query optimization replication Hands-on experience with async job processing (BullMQ Sidekiq Celery or equivalent) and event-driven architecture Comfort with DDD or clean architecture patterns knowing the difference between an entity a service and an infrastructure concern Redis fluency caching patterns pub/sub queue-backed workflows Strong unit and integration testing with Jest writing tests that verify real behavior and hold up under refactor AI Engineering (not AI enthusiasm) Experience building real AI-powered features prompt pipelines LLM API integrations (OpenAI Anthropic Bedrock etc.) and RAG systems Ability to evaluate AI output critically knowing when a model is hallucinating when a generated test is vacuous and when a suggestion will cause a production incident or fail to scale Understanding of AI engineering tradeoffs latency cost reliability correctness and how to design around them Clear opinions on where AI belongs in a software system and where it doesn't Engineering Judgment You write tests that actually test something — colocated integration-level and factory-backed You can read and reason about a migration a query plan or a serializer without needing a prompt You've worked in a codebase with real constraints multi-tenant auth RBAC zero-downtime deployments production databases you can't just rollback You have a point of view on code quality and aren't shy about expressing it in reviews A Note on AI and Engineering Standards We embrace AI tooling and expect engineers to use it well. What we care about is ownership if you ship it you understand it. Our technical assessment and live coding panel are designed to go deep and we'll look at how you think through problems not just what you produce. Engineers who thrive here use AI to move faster without losing their grip on the fundamentals. Nice to Have Prior work in high-throughput transactional systems (POS payments ticketing e-commerce) What to Expect in the Process 1. Initial screen — engineering philosophy system design AI tooling experience 2. Take-home assessment — a scoped backend problem that tests real judgment not just syntax recall 3. Technical panel — live coding architecture discussion code review exercise we'll look at how you think not just what you produce 4. Team conversations — meet the engineers you’d work with every day