Senior Backend Engineer

We're looking for a Senior Backend Engineer to own core infrastructure that powers our platform - from the pipelines that move and process data at scale, to the systems that keep our engineering org shipping fast and reliably. This is a technical leadership role: you'll set architecture direction, raise the bar on engineering practices, and mentor other engineers, while staying deeply hands-on.

You'll operate in an organization that expects AI-native ways of working. Using tools like Claude, Cursor, Hermes or LangGraphor isn't a bonus here - it's the baseline for how we build, and we expect you to help the rest of the team level up on it too.

Responsibilities

Own core backend infrastructure - design and build scalable, reliable Node.js/TypeScript/Python/Go services that other teams and systems depend on.

Build and scale data pipelines - architect the infrastructure that processes and moves large volumes of data reliably, efficiently, and at scale.

Elevate test & validation infrastructure - build the automation, tooling, and CI/CD systems that let engineering ship fast without breaking things, and that make quality and reliability measurable.

Set technical direction - make architecture decisions with company-wide impact, drive design reviews, and establish engineering standards and best practices.

Mentor and multiply - level up other engineers technically, and help shape a fast, high-ownership engineering culture as the team grows.

Lead with AI-native workflows - use AI-assisted development tools daily to move faster without sacrificing architectural quality, and champion their adoption across the team.

Requirements

8+ years of backend software engineering experience, including end-to-end ownership of production systems at scale.

Deep expertise in Node.js and TypeScript, with strong software architecture skills for building modular, distributed systems.

Strong cloud and infrastructure experience (AWS, Kubernetes, Docker), including CI/CD, observability, reliability, and production operations.

Experience building and scaling data-intensive systems, including high-throughput data pipelines, distributed APIs, data modeling (SQL & NoSQL), and messaging platforms such as Kafka or Spark.