Senior Backend Engineer
Monte Carlo Data · Remote, US
About this role
## 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 deploy thousands of agents across business-critical use cases, Monte Carlo provides the reliability infrastructure to support that AI transformation—from human-guided agents to fully autonomous operations. Founded in 2019 and backed by leading investors, Monte Carlo helps data and AI teams ship trusted AI at scale. Learn more: https://montecarlo.ai --- ## The Role We’re hiring a **Senior Fullstack Engineer** to build the core of our agent trust platform: **backend services, distributed systems, and agentic workflows** that help enterprises monitor and trust AI in production. You’ll get a **problem statement (not a spec)** and take it from **prototype → architecture → tested, deployed product**. The role is **mostly backend**, and you’ll ship **React surfaces** when needed. --- ## What You’ll Do - Take vague problem statements to production: **prototype fast**, choose architecture, **build, test, deploy**, and **own** outcomes after launch. - Build and run **production-grade backend services and APIs in Python** powering Monte Carlo’s core platform and agentic systems. - Design and scale **distributed systems** that remain 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 upfront. - Build and maintain **data pipelines** behind analytics, ML, and customer-facing features. - Partner with product, ML, and infrastructure teams to ship customer value; build **React front ends** when needed to complete the work. --- ## What We’re Looking For - **Backend depth:** 5+ years shipping production backend services. Strong **Python (or equivalent)**. Real experience designing, running, and debugging APIs/services under load. - **Distributed systems:** You’ve built and scaled distributed architectures and understand tradeoffs around **reliability, consistency, and observability**. - **0-to-1 ownership:** You’ve taken ambiguous problems from a blank page to a deployed product (prototype, architecture, build, testing, 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/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. --- ## 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. - Remote-first by design since day one; recognized as a Best Workplace for it. - Competitive compensation, equity, an
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