Software Engineer, Gorgias

• 3+ years as a full-stack engineer, and you've shipped user-facing products end to end — you care about the experience people actually have, not just the API behind it
• Strong full-stack engineering across front-end and back-end (React on the front, services and APIs behind it), with the product instinct to turn capabilities into something approachable and reliable
• Comfortable owning cloud-native infrastructure — Kubernetes, Terraform, CI/CD, container orchestration on GCP — and platform services, not just the UI
• Solid with Python and/or TypeScript/Node.js, and pragmatic about picking the right tool for the job
• You understand system design fundamentals — service boundaries, API contracts, async patterns, relational data
• You have a platform mindset: your teammates and Gorgians are your users — and so are the coding agents working in your codebase. You optimize for the productivity and autonomy of all three, writing clean, well-tested, agent-legible code and caring about long-term quality, not just shipping fast
• You're comfortable with ambiguity, communicate clearly, flag blockers early, and own your work end to end

Desirable

• You'll join our platform group and own, end to end, the systems and surfaces that make the whole company effective with AI — from the UI experience people use to the infrastructure it all runs on
• Enhance the Cortex UX. Design and ship the user-facing surfaces of the platform — the work hub, agent/app builder, workflows, connectors, embedded apps — with the product polish and reliability that make people want to use it
• Own platform services and infrastructure. Internal APIs, background workers, integration layers; deployment pipelines on Kubernetes, GitHub Actions, Terraform, and ArgoCD/GitOps; Datadog monitoring, alerting, incident response, and capacity planning
• Build the foundation for others to build on Cortex. The auth, integrations, and app framework that let other teams ship internal apps inside Cortex without touching the infrastructure underneath
• Harden governance and cost control. Permissions, usage visibility, and the controls that let us empower people without overspending on LLM infrastructure
• Raise the bar on developer, agent, and user experience. Reduce friction for AI and Context engineers, automate repetitive work, and keep the platform a place people reach for, not around. Just as important: make the codebase a place coding agents operate efficiently — clear conventions, tooling, docs, and fast feedback loops so agents can ship reliably with minimal hand-holding. We embrace AI-native workflows, and an agent-legible codebase is a first-class goal, not an afterthought
• Be a pillar of the platform. Continuous peer review and shared coverage so the platform is never a one-person operation, and so AI and Context engineers can stay focused on enablement and use cases