Software Engineer - Internal AI Platform

About the role

Software Engineer - Internal AI Platform We believe conversations will become the #1 way to shop. At Gorgias, we’re building the platform that makes this real: a unified AI agent that sells, supports, and re-engages customers across the entire journey. Conversational Commerce is the future of ecommerce, and we’re leading that shift. Our mission is to turn every interaction between a brand and its customers into a relationship: personal, seamless, and intelligent. By combining deep product expertise with the latest in AI, we’re making shopping feel more natural, human, and connected than ever before. To win, we focus relentlessly on: - Quality: conversations that feel authentic and on-brand. - Experience: effortless shopping from chat to checkout. - Re-engagement: personal, 1-1 dialogue instead of noisy marketing. The opportunity is massive. As AI reshapes how people buy, Gorgias is building the foundation for the next decade of ecommerce, where every brand has its own intelligent agent and every customer feels understood. Join us to make Conversational Commerce real. About the team We are the company-wide platform and empowerment team for internal AI at Gorgias. Our mission: make Gorgias the company that operates best with AI — every employee exponentially more productive, every team able to build, and the whole thing governed without friction. We build the platform and we make it land; building is half the job, getting it into everyone's daily work is the other half. We own two layers: - The internal AI Infrastructure — the agent framework, runtime, evals, MCP servers, the skill registry, the Context Layer, governance, deployment and observability. The substrate everything else is built on. - Cortex — the internal AI Platform: the surface where employees work with AI on Gorgias problems, and increasingly where they build with it (agents, workflows, embedded apps), across Slack, the web app, automations, and the API. We sit at the intersection of data, AI, and engineering, with three complementary roles: Platform engineers (this role), who build the infrastructure, services, and surfaces everything runs on; AI engineers, who design and ship the agentic systems; and Context engineers, who structure the data and knowledge that make those systems useful. Enablement and product sense are part of every role here — we treat the platform as a product, and Gorgians are our customers. What you'll do 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. Who you are - 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. Nice to have - Experience building multi-user products — auth, permissions, account management. - Observability and monitoring tooling (Datadog, OpenTelemetry). - Familiarity with streaming infrastructure (Kafka, Kafka Connect, CDC patterns). - Prior platform-engineering or internal-tools experience. - Interest in or exposure to AI-native development — agent orchestration, MCP, evals (LangGraph, LangSmith). Helpful, not required: we can teach the AI layer faster than years of product, web, and infra craft. Our current stack - Agent platform: LangChain / LangGraph - LLM providers: Anthropic, Google...

Key responsibilities

• check_circleCollaborate with the team on day-to-day project tasks
• check_circleLearn tools and processes used by the organization
• check_circleDocument work and participate in team meetings
• check_circleSupport quality checks and continuous improvement

Requirements

• check_circleQuality: conversations that feel authentic and on-brand.
• check_circleExperience: effortless shopping from chat to checkout.
• check_circleRe-engagement: personal, 1-1 dialogue instead of noisy marketing.
• check_circleThe internal AI Infrastructure — the agent framework, runtime, evals, MCP servers, the skill registry, the Context Layer, governance, deployment and observability. The substrate everything else is built on.
• check_circleCortex — the internal AI Platform: the surface where employees work with AI on Gorgias problems, and increasingly where they build with it (agents, workflows, embedded apps), across Slack, the web app, automations, and the API.
• check_circleEnhance 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.
• check_circleOwn 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.
• check_circleBuild 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.
• check_circleHarden governance and cost control. Permissions, usage visibility, and the controls that let us empower people without overspending on LLM infrastructure.

Skills & keywords

Benefits & perks

• check_circleMentorship
• check_circleCertificate of completion
• check_circleFlexible work arrangement where applicable