Senior Full-Stack Engineer

If you’re ready for the next big step in your software development career, read on.

xpander.ai is the platform enterprises use to run AI agents in production. Not to prototype them. To run them, with the connectors, permissions, audit trails, and runtime that a bank, an insurer, or a defense agency actually requires before anything touches a real system.

Our platform is running today inside insurance, fintech, and enterprise software companies, the kind of environments where “it worked in the demo” is not a shipping criterion. We’re a small team, past the first customers, and now building the thing that has to hold at scale.

We are one of very few companies in the world building full-stack AI agent infrastructure. This is your chance to design, own, and scale the systems that power AI agents across every industry, under real enterprise constraints: on-premises and VPC deployments, strict data boundaries, audit requirements, and customers who will read your permission model line by line.

It’s also a role where you will be building software with coding agents, every day. We don’t treat that as a novelty or a productivity hack we’re evaluating. It’s how our engineering works, and it’s a large part of what we ship to customers. We need someone who has already internalized this. Someone who knows how to decompose work for an agent, when to hand off and when to write it yourself, how to review generated code with real rigor, and how to keep architectural coherence when the volume of code going into a repo goes up by an order of magnitude.

If you’ve been shipping production systems this way and have opinions about what breaks, you’re the person we’re looking for.

You’ll work across the frontend and backend systems that form the backbone of the platform: responsive, scalable interfaces on one side, and reliable backend services and APIs on the other. Our stack is Python, React, Type Script, and FastAPI, with PostgreSQL, MongoDB, and Redis, all running on Kubernetes, with an emphasis on performant, secure, and reliable systems.

You’ll work directly with product, design, and the rest of engineering, on a team small enough that you’ll shape the architecture and the roadmap, not just execute against them.

Develop and maintain the core architecture of our AI agent platform, across both frontend and backend

Design and deploy scalable APIs, microservices, and backend systems in Python (FastAPI, Flask, or Django)

Build high-quality, responsive UIs in React and Type Script: reusable components, optimized for performance and accessibility

Build with coding agents as a primary mode of work, and help define how our team does it well, including tooling, review standards, and the guardrails that keep quality high

Own features end to end, from architecture through production deployment. Yes, this means brand new pillars in the platform

Maintain high code quality through testing, code review, and clear standards, which matters even more given how much code we generate

Minimum 7 years as a full-stack engineer on production-grade systems

Substantial hands-on experience building production software with coding agents (Claude Code, Cursor, Codex, or equivalent). We’ll want to talk in detail about what you’ve shipped this way, where the approach failed you, and how you handle review and architectural drift

Proficiency in React, Type Script, and modern frontend patterns (custom hooks, reusable components)

Strong Python backend experience, particularly with FastAPI, Flask, or Django

Proven expertise designing and building scalable APIs and backend systems

Familiarity with relational and non-relational databases (PostgreSQL, MongoDB, Redis)

Familiarity with CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes)

Hands-on AWS experience architecting and deploying applications

Experience with complex UI components such as chat-based systems, drag-and-drop interfaces, or graph and workflow editors

Experience with MCP, agent frameworks, or LLM application infrastructure

Experience building for enterprise constraints: SSO, RBAC, audit logging, self-hosted deployments