jobapplier

Senior Backend Engineer

Monte Carlo

Skills

Required

  • Distributed systems
  • cloud
  • data pipelines / data-heavy systems
  • AWS
  • cloud-native services
  • PySpark
  • ML platform

Preferred

  • backend
  • React
  • Frontend
  • APIs
  • Python
  • ML
  • build React front ends

Join our team as a Senior Backend Engineer and help build the core of our agent trust platform. You'll take vague problem statements and turn them into production-ready products, primarily focusing on backend development. You'll design and scale distributed systems, build and maintain data pipelines, and collaborate with various teams to deliver customer value. The ideal candidate has 5+ years of experience in backend development, a strong understanding of distributed systems, and experience with data pipelines and cloud services.

Responsibilities

  • Prototyping and developing backend services and APIs in Python for the agent trust platform.
  • Designing and scaling distributed systems to ensure reliability, observability, and performance as customer data grows.
  • Collaborating with product, ML, and infrastructure partners to deliver customer value and build React front ends when needed.
  • 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
  • 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

Requirements

  • Distributed systems. You've built and scaled distributed architectures yourself and know the tradeoffs around reliability, consistency, and observability from running them in production
  • 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

Preferred

  • Fullstack range. Frontend experience, ideally React, so you can ship the whole feature. Experience with agentic or LLM-powered systems is a strong plus

Pay

USD 180,000 - 230,000