Senior Backend Engineer - Backend Platform (USA Only, 100% Remote)

About Us

Since 2013, we’ve been building a CRM that gets out of your way and helps your team sell more, faster. Now we’re building AI into every part of it, so Close does the busywork and your team does the selling. No manual data entry, no 10-click workflows. Just communication-first, AI-powered sales software designed to help you succeed and scale.

We're bootstrapped and profitable which means we answer to our customers and play by our rules. We're proud of our 120-person, 100% remote team, focused on building Close so that no small, scaling business fails because it can't figure out sales.

Our Stack

Our backend tech stack consists primarily of Python Flask web apps with our TaskTiger scheduler handling many of the backend asynchronous task processing chores. Our data stores include MongoDB, PostgreSQL, Elasticsearch, and Redis. The underlying infrastructure runs on AWS using a combination of managed services like EKS, MSK, RDS and ElastiCache and non-managed services running on EC2 instances. We have CI/CD pipelines that build Docker images, run automated tests and deploy to Kubernetes clusters. We also use these images in our local development environment allowing coding locally against all of our services. We have a well-documented public API that is consumed by our front-end JavaScript app as well as numerous integrations. Our infrastructure is heavily automated using Terraform, Ansible and other AWS tools.

We love open sourcing our code and ideas on our GitHub and on The Making of Close , our behind-the-scenes Product & Engineering blog. Check out our open source projects like SocketShark , TaskTiger , LimitLion and ciso8601 .

AI is both how we build and what we ship, and that's reshaped what engineering looks like. This is a transformation we’re embracing and find deeply exciting.

About the Role

Close runs on Python: Flask web apps, TaskTiger, billions of MongoDB documents, a public REST API that customers and external agents both build on. Four product teams ship features on top of that every week. Backend Platforms owns the foundation underneath it all.

As an Engineer on our Backend Platforms team, you’re building for other engineers. When a product team adds a new API endpoint, most of what they write isn't their feature — it's wiring: authentication, permissions, rate limiting, the shape the endpoint has to take so it looks like every other endpoint when you squint. Multiply that across telemetry, eventing, database migrations, authorization, and local development, and you get the problem this team exists to solve: make the paved road faster to walk than the trail.

The other half of the team's mandate is the AI development platform. We've built DevDawg, cloud-based development environments preconfigured for our entire application stack and our engineering practices, and Spice, our extension layer on top of a coding agent that runs internal review workflows and root cause analysis. Spice is hooked into GitHub and can already approve mergeable pull requests on its own for simple changes. This team is responsible for expanding what it can safely handle.

This is a new team. You would be one of the first hires, and you'd have unusual influence over what the team owns and how it operates.

One thing to know: we do move people between teams as the work shifts. Most engineers here end up on more than one team over their time at Close — this team is where you'd start, but over time you'll likely have the opportunity to work on many different projects.

This role is open at the Senior and Staff levels. You don't need to pick one when you apply: we'll calibrate together during the process.

You are

A seasoned Python engineer. Python is our backbone and it matters in this role more than on other teams at Close. Architectural patterns don't port cleanly between languages, and you'll be setting the patterns. Go, Rust, or TypeScript alongside it is welcome.

Drawn to meta-problems. This team doesn't ship features to customers; it changes how features get built.

AI-native in production. You've shipped meaningful LLM-backed or agentic work to real users. For a team building AI tooling that other engineers depend on, this is foundational to the role.

Working with AI in your day-to-day. You use coding agents in your own workflow and have a real POV on where they help and where they get in the way. On this team, your POV becomes the product. We fund best-in-class developer tools and treat experimentation as part of the work.

Fluent in observability and production practice. Telemetry, metrics, tracing, alerting, Sentry ownership, what production-ready actually means. You've been the person who made a system legible when it broke.

Opinionated about API design. You've shipped internet-facing APIs and you think about who's on the other end — apps, agents, humans reading docs — and what each needs.

Battle-tested. You've debugged incidents where latency budgets didn't hold, owned a system everyone else relied on, or carried a pager for something with real customer impact.

A builder first. You'd rather get a rough v1 in front of five engineers than spend three weeks on abstractions.

Energized by internal customers. Your users are a Slack DM away. You'll talk to them directly instead of through a PM, and you'll use most of what you build yourself.