Senior Backend Engineer

Posted 2 Hours Ago
Hiring Remotely in US
Remote
180K-230K Annually
Senior level
Big Data • Cloud • Software • Generative AI • Big Data Analytics
Monte Carlo is the agent trust platform that monitors, troubleshoots, and improves production AI systems.
The Role
Build and operate production-grade Python backend services, APIs, distributed systems, data pipelines, and agentic workflows for an AI observability platform. Own ambiguous projects from prototyping through architecture, testing, deployment, and ongoing operation. Collaborate with product, machine learning, and infrastructure teams, while contributing React front ends when needed. The role requires strong backend depth, distributed-systems expertise, cloud experience, and end-to-end product ownership.
Summary Generated by Built In

About Monte Carlo

Monte Carlo is the agent trust platform that unifies data and agent observability to monitor, troubleshoot, and improve production AI systems. As enterprises prepare to deploy thousands of agents across business-critical use cases, Monte Carlo provides the reliability infrastructure to support them along this AI transformation, from human-guided agents to fully autonomous operations. Founded in 2019 and backed by leading investors, Monte Carlo empowers data and AI teams to ship trusted AI at scale. Learn more at montecarlo.ai

The Role

We're hiring a Senior Fullstack Engineer to build the core of our agent trust platform: the backend services, distributed systems, and agentic workflows that let enterprises monitor and trust AI in production. You'll get a problem statement, not a spec, and take it from prototype to architecture to a tested, deployed product. The role is mostly backend, and you'll ship the React surfaces that go with it when the work calls for it.

What You'll Do
  • Take vague problem statements to production: prototype fast, pick the architecture, build it, test it, deploy it, and own it after launch.

  • Build and run production-grade backend services and APIs in Python 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.

  • Start with simple, flexible designs and evolve them as the product and company scale, 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 build React front ends where they're needed to finish the job.

What We're Looking For
  • Backend depth. 5+ years shipping production backend services. Strong Python or an equivalent backend language, and real experience designing, running, and debugging APIs and services under load.

  • Distributed systems. You've built and scaled distributed architectures yourself and know the tradeoffs around reliability, consistency, and observability from running them in production.

  • 0-to-1 ownership. You've taken ambiguous problems from a blank page to a deployed product: prototype, architecture, build, testing, and deploy. You move with urgency and treat outcomes as yours.

  • Data and cloud. Experience with data pipelines or data-heavy systems on AWS and cloud-native services. PySpark and ML platform experience are a plus.

  • Fullstack range. Frontend experience, ideally React, so you can ship the whole feature. Experience with agentic or LLM-powered systems is a strong plus.

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, not distributed systems you've scaled and run.

  • 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.

We are proud to be recognized for our world-class employee experience:

Monte Carlo Named 2025 Databricks Data Governance Partner of the Year

We were recently recognized as the #1 Data Observability Platform by G2 for the 4th consecutive quarter. See our G2 reviews here!

Monte Carlo Named to G2's Best Software Products of 2026

Monte Carlo was featured on Database Trends and Applications (DBTA’s) Trend-Setting Products for 2025!

We are super proud to be named the 2026 Best Place to Work by Built In!

Beware of Imposter Recruiters and Job Scams

  • All official communication from our recruiting team will come from an @montecarlodata.com email address.

  • We will never ask candidates to provide sensitive personal information (such as bank details, social security numbers, or payment) at any stage of the recruitment process.

  • We will never request payment for equipment, training, or application processing.

  • Our open positions are always listed on our official careers page: https://jobs.ashbyhq.com/montecarlodata.

If you are contacted by someone claiming to represent Monte Carlo but you’re unsure of their legitimacy, please reach out to us directly at [email protected] before sharing any personal information.

Skills Required

  • 5+ years shipping production backend services
  • Strong Python or equivalent backend language experience
  • Experience designing, running, and debugging APIs and services under load
  • Experience building and scaling distributed architectures
  • Experience taking ambiguous problems from prototype through architecture, development, testing, and deployment
  • Experience with data pipelines or data-heavy systems on AWS and cloud-native services
  • Frontend experience, ideally with React
  • PySpark experience
  • Machine learning platform experience
  • Experience with agentic or LLM-powered systems

What the Team is Saying

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The Company
HQ: San Francisco, CA
135 Employees
Year Founded: 2019

What We Do

Monte Carlo is the agent trust platform that unifies data and agent observability to monitor, troubleshoot, and improve production AI systems. As enterprises prepare to deploy thousands of agents across business-critical use cases, Monte Carlo provides the reliability infrastructure to support them along this AI transformation, from human-guided agents to fully autonomous operations. Founded 2019. Backed by leading investors. Trusted by 400+ enterprises including Amazon, PepsiCo, CNN, Nasdaq, and JetBlue.

Why Work With Us

A Built In 2026 Best Place to Work, Inc. Best Workplace 2024, and Newsweek Most Loved Workplace. We're remote-first, solving one of the biggest problems in the AI era: trust. We build fast, ship bold, and have a great time doing it. Come help the world adopt trusted AI.

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Monte Carlo Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Remote-first, local-second. We hire the best person for the role wherever they are, default to async, and cover coworking for everyone. Dedicated offices in eight cities for anyone who wants an in-person day. None of them required.

Typical time on-site: Not Specified
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