About Monte Carlo

Monte Carlo is the agent trust platform that autonomously observes, fixes, and continuously improves agents and the data that powers them — so enterprises can scale trust at the speed of AI. Bayes, our AI teammate, does the work: detecting, triaging, troubleshooting, and fixing issues in AI agents and the data powering them. The result is self-improving agents that get better with every fix instead of drifting. More than 400 enterprises, including Amazon, PepsiCo, CNN, Nasdaq, and JetBlue, rely on Monte Carlo. Learn more at montecarlo.ai.

The Role

We're hiring a Senior Backend Engineer to design and build the core of our agent trust platform: the architecture, distributed systems, and backend services that let enterprises trust AI in production. You'll get a problem statement, not a spec, and own it from system design to a tested, deployed product. React experience is a plus for the times a feature needs a front end.

What You'll Do

Own the architecture and system design for core platform services: make the calls, write down the tradeoffs, and evolve the design as scale grows.

Build and run production-grade backend services and APIs in Python or Java that power Monte Carlo's core platform and agentic systems.

Design and scale distributed systems that stay reliable, observable, and fast as customer data and agent volume grow.

Take vague problem statements to production: prototype, architect, build, test, deploy, and own it after launch. Start simple and evolve it without over-building up front.

Build and maintain data pipelines behind analytics, ML, and customer-facing features.

Work with product, ML, and infrastructure partners to ship customer value, and pick up React work when a feature needs it.

What We're Looking For

Backend depth. 5+ years shipping production backend services in Python or Java, with real experience designing, running, and debugging APIs and services under load.

Architecture and system design. You've designed systems from a blank page, weighed the options, and can defend the tradeoffs: consistency, availability, latency, and cost.

Distributed systems. You've built and scaled distributed architectures yourself and run them in production: services, queues, event-driven flows, data stores, and what happens when they fail.

0-to-1 ownership. You've taken ambiguous problems to a deployed product, owned testing and deploy, and kept owning it after launch. You move with urgency and treat outcomes as yours.

Nice to have. React for the times a feature needs a front end. Agentic or LLM-powered systems in production are a strong plus, as are data pipelines on AWS and PySpark.

This Is Not For You If

You want a detailed spec before you start building.

Your backend experience is mostly CRUD apps on a single service, or you've only built inside architectures someone else designed.

You'd rather hand off testing, deployment, and on-call than own them.

You're mainly a frontend engineer looking to grow into backend.

#LI-REMOTE

#BI-REMOTE

Why Monte Carlo

We created the data observability category, and we're doing it again with agent trust — you'll build where the market is forming, not where it's settled

Series D, $236M raised, backed by Accel, Redpoint, Notable Capital, ICONIQ Growth, and Salesforce Ventures

Customers include HubSpot, Fox, Nasdaq, Toast, and Mercado Libre — your work ships to enterprises with real stakes

Snowflake Partner of the Year and a verified connector in Anthropic's Claude AI directory

Remote-first by design since day one, and recognized as a Best Workplace for it

Competitive compensation, equity, and a remote-first environment.

Come As You Are

Equality is a core tenet of Monte Carlo's culture. We are committed to building an inclusive global team that represents a variety of backgrounds, perspectives, beliefs, and experiences.

Monte Carlo is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.