Senior Backend Engineer
Monte CarloRemoteposted 12d ago
- PayUSD / yr
- $180k – 230k
- Where
- Remote (US)
- Posted
- Sep 30
- 12 days ago
- Type
- Full-time
- Setup
- Remote
At a glance
Build and operate Python backend services, distributed systems, data pipelines, and agentic workflows powering Monte Carlo’s AI observability platform, taking ambiguous ideas from prototype through production.
Summarized by AI from the original posting
What you'll do
- Take vague problem statements from prototype to production
- Build and run Python backend services and APIs
- Design and scale distributed systems
- Build and maintain data pipelines
- Work with product, ML, and infrastructure partners
- Build React front ends as needed
- Own testing, deployment, and post-launch operation
Requirements
- 015+ years shipping production backend services
- 02Strong Python or equivalent backend language
- 03Experience designing, running, and debugging APIs and services under load
- 04Experience building and scaling distributed architectures
- 05Experience taking ambiguous problems from prototype to deployed product
- 06Experience with data pipelines or data-heavy systems on AWS
- 07Frontend experience, ideally React
- 08Agentic or LLM-powered systems experience is a plus
Perks
Skills
Full 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
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
Monte Carlo Named to G2's Best Software Products of 2026
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 recruiting@montecarlodata.com before sharing any personal information.
Compensation: $180K - $230K