Sr Python Engineer

CargoSprint

19h

About The Position

This role is part of a small, senior team building the automation and agent layer that powers CargoSprint's next phase of growth. You will work closely with principal engineers and product leadership to build backend services that are reliable, fast, and easy to maintain. You take ideas to production, own what you ship, and improve it over time. Startup mindset within a PE-backed company on a mission to Empower the people who make global commerce happen.

Requirements

Clear, professional communication skills in English — written and verbal
Ability to self-manage and stay productive with limited day-to-day oversight
Strong ownership mentality — you care what happens after you merge the PR
Experience working in a startup or fast-paced, high-growth environment
A genuine interest in building things that users actually use and appreciate
Comfortable asking for help when you need it and unblocking yourself when you can
Strong Python proficiency — you write idiomatic, readable, maintainable code and you know why it matters
Experience building backend services and REST APIs — FastAPI or a similar framework; you understand how APIs are designed, not just how to write endpoints
Solid Postgres skills — schema design, query writing, understanding of indexes and performance basics
Good testing habits — you write unit tests as part of the work, not as an afterthought
Working knowledge of DevOps concepts — Docker, CI/CD pipelines, deployment basics; you have shipped to production and supported what you shipped
Strong Familiarity with AI coding tools — Cursor, Copilot, or similar; you use them to go faster, not as a substitute for understanding what you're building

Nice To Haves

Familiarity with Temporal
Familiarity with Kubernetes
Familiarity with Pulumi
Familiarity with Vue.js

Responsibilities

Build and maintain backend services and APIs using Python, FastAPI, and Temporal — writing clean, tested, production-ready code
Work with Postgres to design schemas, write efficient queries, and keep data performant as usage grows
Write solid unit tests and participate in code reviews that help the whole team ship with more confidence
Apply DevOps fundamentals — containerization, CI/CD pipelines, deployment, and basic monitoring — to keep what you build running well
Take well-scoped features from implementation to production and iterate based on real-world feedback
Use AI coding tools to accelerate your own development and bring that productivity mindset to the team
Debug production issues methodically and implement fixes that actually stick
Collaborate with principal engineers on architecture decisions and contribute your perspective — you are not just executing tickets