---
title: 'Senior Backend Engineer at Monte Carlo'
canonical: 'https://feeny.ai/job/senior-backend-engineer-monte-carlo-united-states-mnmxvcd5sns7'
type: 'job'
last_seen: '2026-10-13'
---

# Senior Backend Engineer at Monte Carlo

- **Company:** Monte Carlo
- **Location:** United States
- **Compensation:** $180k–$230k
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-09-30
- **Last confirmed live:** 2026-10-13
- **Apply:** https://jobs.ashbyhq.com/montecarlodata/ea86bb66-c471-4e7e-b0f1-42d1c78dc2d1

## Job description

## 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](https://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](https://montecarlo.ai/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](https://www.montecarlodata.com/blog-2025-databricks-data-governance-partner-of-the-year/?utm_source=chatgpt.com) [We were recently recognized as the #1 Data Observability Platform by G2 for the 4th consecutive quarter. See our G2 reviews here!](https://www.g2.com/reports/grid-report-for-data-observability-spring-2025.embed?featured=monte-carlo&secure%5Bgated_consumer%5D=7d02ec0a-326a-40fa-8a44-fab49f67c5f1&secure%5Btoken%5D=6b3c29d18ea50ae0005295b5c63994f97c01cae81bbd3f9ea6abff73c40fde51&utm_campaign=gate-2063400) [Monte Carlo Named to G2's Best Software Products of 2026](https://www.montecarlodata.com/blog-monte-carlo-g2-best-software-product-of-2026/) https://www.dbta.com/Editorial/Trends-and-Applications/Trend-Setting-Products-in-Data-and-Information-Management-for-2025-167115.aspx [We are super proud to be named the 2026 Best Place to Work by Built In!](https://builtin.com/awards/us/2026/best-places-to-work) Beware of Imposter Recruiters and Job Scams

- All official communication from our recruiting team will come from an @[montecarlodata.com](http://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 recruiting@montecarlodata.com before sharing any personal information.

## About Monte Carlo

## Company Overview
- **One-liner**: Monte Carlo provides an autonomous observability platform that unifies data and agent observability to monitor, troubleshoot, and improve production AI systems.
- **Entity Type**: Private (Series D, $135M raised May 2022)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2019
- **Founders**: Not publicly listed as founders in provided sources (likely Lior Gavish as CTO and others; not explicitly named)

## Core Business
- **Primary industries**: Data infrastructure, AI observability, Software Development
- **Target customers**: Enterprise B2B – data and AI teams at large organizations (400+ enterprise customers including JetBlue, Roche)
- **Mission / purpose**: "Reduce data downtime" and enable enterprises to ship trusted AI at scale by providing reliability infrastructure for agents and data pipelines.

## Products & Services
- **Monte Carlo Platform**: An end-to-end autonomous observability platform that monitors data pipelines, agents, and AI systems in production. Includes features like anomaly detection, data lineage, and incident resolution. Type: SaaS.
- **Agent Trust Platform**: A newer capability focused on monitoring and troubleshooting AI agents in production, unifying data observability with agent observability.

## Market Standing
- **Valuation / Market Cap**: Not disclosed (private); total funding $236M (Seed, Series A $16M, Series B $25M, Series C $60M, Series D $135M)
- **Key Metric**: Total Funding $236M; Annual Revenue reported as $2M (likely placeholder/outdated – LinkedIn often shows symbolic revenue). 400+ enterprise customers, 10M tables monitored, 1,000 incidents resolved daily.
- **Notable Investors/Partners**: Accel (lead in Seed & Series A), Redpoint, Notable Capital (Series B), ICONIQ Growth (Series C), IVP (Series D). Partners include Alation, Sigma, Fivetran, Snowflake, Databricks.
- **Growth Signals**: +9.8% YoY headcount growth (212 employees), operates in 14 countries, recent launch of "Trusted Data for AI (TDAI) Advisory Council" (Aug 2024), support for Apache Kafka and vector databases (Nov 2023). Recognized by Forrester with a TEI study showing 375% ROI and $1.5M avoided losses.

## Competitive Advantages
- First-to-market autonomous observability platform combining data and agent monitoring.
- Deep integrations with modern data stacks (Snowflake, Databricks, dbt, Fivetran, Kafka) and AI frameworks.
- Strong enterprise adoption (JetBlue, Roche) and validated ROI (Forrester study).
- 80% reduction in data downtime reported by customers.

## Strategic Focus
- Expanding from data observability to "agent trust" to support the explosion of AI agents in production.
- Building out the "Monte Carlo for AI" go-to-market, with a dedicated Advisory Council.
- Scaling global presence (14 countries) and deepening partnerships with major cloud and data platforms.

## Why Work Here
- **Culture**: Values include "Measure in minutes" (urgency), "Ship and iterate" (high expectations with iteration), "Customer impact", and "Beat the odds" (ambition, learning from failure). Emphasizes a positive, team-oriented environment.
- **Work policy**: Not explicitly stated as fully remote, but based on LinkedIn locations (HQ in San Francisco, offices in multiple US cities, and distributed teams across 14 countries) it likely supports hybrid/remote. The careers page mentions "Global Office and Culture Manager".
- **Engineering culture**: High degree of execution and collaboration; tech stack includes Python, TypeScript, React, GraphQL, Snowflake, Databricks, and modern observability tools (DataDog, PagerDuty). Employees come from top tech companies (Google, Snowflake, Twilio, Confluent).
- **Perks**: Not detailed in public sources, but the "Have fun" value and focus on authenticity suggest a strong culture. Recent departures of some senior sales and marketing leaders may indicate restructuring.
- **Candidate note**: Official communication only from @montecarlo.ai emails; beware of scams.

## Sources
1. [montecarlo.ai - About Us](https://montecarlo.ai/about-us)
2. [montecarlo.ai - Homepage](https://montecarlo.ai/)
3. [Monte Carlo Careers](https://www.montecarlodata.com/careers-at-monte-carlo/)
4. [LinkedIn Company Profile](https://www.linkedin.com/company/monte-carlo-data)

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