Senior Backend Engineer

Monte Carlo
•$180,000 - $230,000•Remote

About The Position

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 1999 and backed by leading investors, Monte Carlo empowers data and AI teams to ship trusted AI at scale. 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.

Requirements

  • 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.
  • You've built and scaled distributed architectures yourself and know the tradeoffs around reliability, consistency, and observability from running them in production.
  • 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.
  • Experience with data pipelines or data-heavy systems on AWS and cloud-native services.
  • Frontend experience, ideally React, so you can ship the whole feature.

Nice To Haves

  • PySpark and ML platform experience are a plus.
  • Experience with agentic or LLM-powered systems is a strong plus.

Responsibilities

  • 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.

Benefits

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