About Us

At Rox, we believe in empowering people to do their best work.

Our platform supercharges sellers with autonomous revenue agents to do the manual work so they can focus on what they do best: selling. Just as coding agents 10x’d engineering, revenue agents 10x customer work.

We are reimagining the revenue stack by building the world’s first revenue operating system, from the application layer to the system of context. With Rox, humans are evolving to orchestrators while agents manage the end-to-end customer lifecycle.

Rox powers Global 2000 leaders in banking, hardware, construction, and sovereign AI, while serving dominant AI winners like Ramp and Cognition.

Underlying all of this success is an unwavering, shared belief in the mission, with an unreasonable commitment of doing whatever it takes to make it a reality.

The Team

Nothing is possible without the world-class team, assembled to redefine how businesses operate.

Members on our team have:

Founded and exited successful companies

Held the highest positions at Google, AWS, Confluent, and New Relic

Won IMO and IOI gold medals

Published field-defining papers

We’re backed by the best, including Sequoia, General Catalyst, Google Ventures, Elad Gil, and Chris Ré.

Core Principles

Taste: Craft beautiful experiences.

No matter how small, we strive to make sure every detail is right. We care deeply about every interaction, both in terms of whether it helps the seller get the job done, but also how the product makes them feel. We get a visceral feeling when something is off and stop at nothing to make sure we make it right. We never settle, continuously exploring ways to delight sellers.

Obsession: Commit unreasonably.

In all aspects of our craft, we commit. We not only are immediately reactive to customers’ requests but are proactive about driving value even before they ask. We are also obsessive about always learning and honing our craft, improving ourselves and product every single day.

Action: Get it done.

Talking is easy but the difference comes from the execution. We lean heavily towards making thoughtful yet fast decisions and delivering immediately. We play in a field where trust is paramount. We earn the trust and right to empower the best sellers by forging a history of over-delivering on the promise at record speed.

Your Role

About the Core Engineering Team

Core Engineering builds the systems that make autonomous revenue agents reliable at enterprise scale.

This team sits at the center of Rox’s long-term technical strategy and owns foundational infrastructure across:

agent reliability and orchestration

distributed execution systems

graph-based retrieval infrastructure

streaming and real-time context systems

observability for autonomous workflows

low-latency data and inference pipelines

The problems here look less like traditional SaaS application engineering and more like:

real-time OLAP systems

streaming compute platforms

distributed databases

semantic retrieval systems

deterministic execution infrastructure

high-scale platform engineering

At Rox, agents continuously:

retrieve context

reason across changing state

trigger actions

update workflows

coordinate across systems

Core Engineering builds the infrastructure that makes those loops fast, reliable, observable, and deterministic.

The Role

We are hiring a Core Engineer to help design and operate the foundational infrastructure behind Rox’s autonomous agent platform.

This role is ideal for engineers who have deep systems intuition and want to work on infrastructure problems at the frontier of AI reliability.

You might be a fit if you’ve spent time building:

distributed infrastructure

streaming systems

semantic search infrastructure

graph-based retrieval systems

execution runtimes

reliability infrastructure

low-latency backend platforms

Or if you’ve historically been “the person” inside your company for difficult infrastructure problems.

We care deeply about engineering craftsmanship, systems thinking, and people who can reason about long-term architecture under real-world scale constraints.