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 montecarlo.ai THE ROLE We're hiring a Senior Backend Engineer to design and build the core of our agent trust platform: the architecture, distributed systems, and backend services that let enterprises trust AI in production. You'll get a problem statement, not a spec, and own it from system design to a tested, deployed product. React experience is a plus for the times a feature needs a front end. WHAT YOU'LL DO - Own the architecture and system design for core platform services: make the calls, write down the tradeoffs, and evolve the design as scale grows. - Build and run production-grade backend services and APIs in Python or Java 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. - Take vague problem statements to production: prototype, architect, build, test, deploy, and own it after launch. Start simple and evolve it 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 pick up React work when a feature needs it. WHAT WE'RE LOOKING FOR - Backend depth. 5+ years shipping production backend services in Python or Java, with real experience designing, running, and debugging APIs and services under load. - Architecture and system design. You've designed systems from a blank page, weighed the options, and can defend the tradeoffs: consistency, availability, latency, and cost. - Distributed systems. You've built and scaled distributed architectures yourself and run them in production: services, queues, event-driven flows, data stores, and what happens when they fail. - 0-to-1 ownership. You've taken ambiguous problems to a deployed product, owned testing and deploy, and kept owning it after launch. You move with urgency and treat outcomes as yours. - Nice to have. React for the times a feature needs a front end. Agentic or LLM-powered systems in production are a strong plus, as are data pipelines on AWS and PySpark. 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, or you've only built inside architectures someone else designed. - 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 montecarlo.ai — 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 montecarlodata.com We were recently recognized as the #1 Data Observability Platform by G2 for the 4th consecutive quarter. See our G2 reviews here! g2.com Monte Carlo Named to G2's Best Software Products of 2026 montecarlodata.com Monte Carlo was featured on Database Trends and Applications (DBTA’s) Trend-Setting Products for 2025! dbta.com We are super proud to be named the 2026 Best Place to Work by Built In! builtin.com Beware of Imposter Recruiters and Job Scams - All official communication from our recruiting team will come from an @montecarlodata.com 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: jobs.ashbyhq.com. 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.

Requirements

Must-haves

Own the architecture and system design for core platform services: make the calls, write down the tradeoffs, and evolve the design as scale grows.
Build and run production-grade backend services and APIs in Python or Java 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.
Take vague problem statements to production: prototype, architect, build, test, deploy, and own it after launch. Start simple and evolve it 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 pick up React work when a feature needs it.
Backend depth. 5+ years shipping production backend services in Python or Java, with real experience designing, running, and debugging APIs and services under load.
Architecture and system design. You've designed systems from a blank page, weighed the options, and can defend the tradeoffs: consistency, availability, latency, and cost.
Distributed systems. You've built and scaled distributed architectures yourself and run them in production: services, queues, event-driven flows, data stores, and what happens when they fail.
0-to-1 ownership. You've taken ambiguous problems to a deployed product, owned testing and deploy, and kept owning it after launch. You move with urgency and treat outcomes as yours.
You want a detailed spec before you start building.
Your backend experience is mostly CRUD apps on a single service, or you've only built inside architectures someone else designed.
You'd rather hand off testing, deployment, and on-call than own them.
You're mainly a frontend engineer looking to grow into backend.
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.

Nice-to-haves

Nice to have. React for the times a feature needs a front end. Agentic or LLM-powered systems in production are a strong plus, as are data pipelines on AWS and PySpark.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aireactpythonjavamlllmaws

Platform: ashby
Effort: quick