Foundations Engineer (Deep Infra, SF in office)

Rox is building the AI-native revenue operating system.

Most enterprise software was built for humans operating dashboards. Rox is built for agents operating systems.

Instead of static workflows, Rox runs continuous decision loops powered by real-time context from across the enterprise.

Agents analyze signals, reason about them, and take action — automatically.

To make that possible, we are building infrastructure that combines elements of:

• distributed data platforms

• real-time decision systems

• agent execution frameworks

• low-latency context retrieval

We’re backed by Sequoia, GV, and General Catalyst and building a small team of engineers who want to work on deep technical systems problems with real-world impact.

The Foundations team builds the core infrastructure behind Rox agents.

We work on the systems responsible for:

• real-time context ingestion

• agent execution and orchestration

• reliability for long-horizon AI tasks

• low-latency decisioning across distributed systems

If you've worked on systems like:

• streaming compute platforms

• distributed query engines

• real-time OLAP systems

• matching engines

• large-scale data infrastructure

many of the problems here will feel familiar — but applied to a new category of software.

At Rox, agents are constantly:

• retrieving context

• making decisions

• triggering actions

• updating state

The Foundations team builds the infrastructure that makes those loops reliable, fast, and observable.

We are hiring a Foundations Engineer (Deep Infra) to design and operate the systems that power Rox’s agent runtime.

This role sits at the intersection of:

• distributed systems

• real-time data infrastructure

• agent orchestration

• decisioning systems

You will work on infrastructure similar to what powers large-scale data platforms — but optimized for continuous AI decision loops rather than batch analytics.

Many of the systems we are building resemble components from:

• streaming compute systems

• distributed query engines

• large-scale event processing pipelines

• matching and routing infrastructure

But with a new constraint: AI agents must operate continuously and reliably in production environments.

Design and build core distributed systems powering Rox agents.

Build infrastructure for real-time context ingestion and retrieval.

Develop systems that enable low-latency agent decisioning at scale.

Improve reliability, observability, and fault tolerance across agent infrastructure.

Build execution frameworks that support long-running agent workflows.

Collaborate closely with product engineers and forward deployed engineers to translate infrastructure capabilities into customer impact.

Ship production systems quickly and evolve them based on real-world usage.

Experience building deep infrastructure systems in production.

Examples include:

• distributed data platforms

• streaming compute systems

• real-time analytics infrastructure

• distributed query engines

• high-scale backend services

Strong intuition for latency, reliability, and scalability tradeoffs.

Experience operating systems where real-world traffic exposes edge cases quickly.

Comfort debugging complex distributed systems in production.

A bias toward shipping systems, learning from production, and improving them continuously.