Monte Carlo

Senior Backend Engineer

Monte Carlo • $135K — $160K *
US-AnywhereRemote in United States
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience shipping production backend services, especially in Python.
  • Proven ability to build and scale distributed architectures with a keen understanding of trade-offs in systems.
  • Experience in taking ambiguous problems from concept to deployed product with a sense of urgency.
  • Familiarity with data pipelines and data-heavy systems, especially on AWS.
  • Frontend experience with React, ideally with knowledge of agentic or LLM-powered systems.

Responsibilities

  • Prototype and transform vague problem statements into deployed products.
  • Develop and run production-grade backend services and APIs using Python.
  • Design scalable and reliable distributed systems to handle increasing customer data.
  • Create flexible system designs and evolve them as the company grows.
  • Build and maintain data pipelines for analytics and customer-facing features.
  • Collaborate with product, ML, and infrastructure teams to deliver customer value, including frontend development when necessary.

Benefits

  • Remote work flexibility with a supportive company culture.
  • Commitment to diversity and inclusion in the workplace.
  • Recognition as a top employer and leader in data observability.
  • Opportunities for professional growth within an innovative environment.
Full Job Description
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

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 before sharing any personal information.

About Monte Carlo

Monte Carlo is a data observability platform that helps companies identify and prevent data downtime. The company's platform uses machine learning to detect anomalies and provide alerts to data teams. Monte Carlo's mission is to help companies trust their data and make better decisions.
Learn more about Monte Carlo
Size
50 employees
Industry
Founded
2020
Revenue
$25 million

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