Software Engineer, Backend (Python)

2 нед. назад

United StatesCanadaWorldwide

python

Develop backend systems with Python for a work management platform used globally.

Обязанности

keeps live work state in sync across thousands of workspaces, including self-hosted clusters we will never see, and that machinery now has to carry agents that read and change state at machine speed. You will work across the Django services behind projects, cycles, issues, and permissions, the event streams and change data capture that push state out to every client, and the caching and query paths that keep a large workspace fast. You will start on scoped surfaces and take on larger ones as you learn the system. All of it ships to Cloud and self-hosted customers from one codebase, so you will design for machines you cannot log into, working alongside product and frontend engineers in San Francisco and Hyderabad.
Own backend surfaces end to end, from API contract and data model through migration and rollout, starting with scoped ones and taking on larger ones as you learn the system.
Extend the real-time sync path alongside the engineers who designed it: event streams, change data capture, and the caching in front of them.
Measure and improve query performance as workspaces grow. Query plans, indexes, and connection pooling are yours to read and fix.
Instrument what you ship so that a degradation shows up in our dashboards before a customer reports it, and take your turn responding when it fires.
Work daily with product and frontend engineers across San Francisco and Hyderabad, and with community members whose issue reports become your test cases.
Debug what you cannot reproduce, on hardware and networks we will never have access to.

Будет плюсом

You have contributed to , run it self-hosted, or maintained another open project people rely on.
You have worked with event streams or message queues (Kafka, RabbitMQ, or similar).
You understand deployment beyond a deploy button: containers, migrations across versions, and what changes when customers run your releases themselves.
You have shipped software into regulated or isolated environments: banking, defense, healthcare, or air-gapped anything.
You have built systems where AI agents act on real data, and you have opinions about state, permissions, and audit trails.

Другое

's mission is to build the infrastructure the world's work runs on. Every organization runs on three things: the projects it's driving, the knowledge it keeps, and the requests it fields. brings all three into one open, adaptable platform: simple enough for any team to adopt, dependable enough for organizations to build on. And we are building it for a future where humans and AI agents do that work together.
began in public on GitHub at the end of 2022. Since then it has grown into a work management platform used by teams around the world: 55,000+ stars, 5,000+ forks, and a contributor community that reads our code and files our issues. Organizations run as a managed Cloud service, on their own infrastructure, or inside fully isolated environments. Building in the open keeps us close to users and raises the standard for everything we ship.
is the #1 work infrastructure in aerospace, defense, financial services, and other regulated industries: organizations whose requirements for control, auditability, and data residency rule most software out. When the strictest buyers pick a system of record, that choice means something. Adoption is growing fastest on Cloud and in sovereign clouds, deployments that keep everything inside a country's own borders and rules.
is backed by top investors and built across San Francisco, London, and Hyderabad. We work in tightly knit teams, stay close to users, and care about the visible product as much as the unglamorous details that make software dependable. People own problems end to end, and we add process only when it helps the work.
We believe the next decade of work will be done by humans and AI agents together. Not agents replacing people, and not a chat window bolted onto software built for humans clicking around, but both working in one system of action, where an agent's work is as visible and as accountable as a person's.
Most software treats AI as a feature. We treat agents as a kind of worker, and that changes what the system underneath has to be. Agents are only as good as the context they can see and the state they are allowed to change, so shared context, explicit state, durable history, and accountable action are not items on our roadmap. They are the product. is built so that when an agent acts, the humans responsible can see what happened, why, and on whose authority, and the record survives.
This is what the infrastructure is for: making the future where humans and agents work together useful, legible, and fully within the organization's control. Every role at is some part of building that.
You have shipped Python to production. Point us to something you built, and tell us one decision in it you would make differently now.
You have worked in Django or a comparable framework. Models, migrations, and the request cycle are familiar rather than new.
You are comfortable in SQL, not only the ORM. You can read a query, add an index, and say why it helped.
You have written async Python. asyncio in something that carried real traffic, not only in a tutorial.
You have debugged something in production. A real incident, and what you changed because of it.
You write clearly. A public issue thread gets better when you show up in it.
Backend: Python, Django, FastAPI, Golang, Node.js, Postgres, Redis
Messaging: RabbitMQ, Kafka
Infrastructure: AWS, Kubernetes, Rancher
Observability: Datadog, Sentry
Everyday tools: GitHub, (yes, we run on it), Figma, Slack
Every company says it is different. We will try evidence instead.
The scope is real. We are a passion team serving companies of every size, including some of the largest in the world. Something you ship this month will run inside a Fortune 500 company and a 50-person startup in the same week, and you will hear from both.
The constraints make you better. runs in our cloud, in customers' clouds, and on machines that will never touch the internet. Much of the work happens in the open, where the issues, the fixes, and the roadmap conversations are public. Building software that survives all of that is harder than building an ordinary SaaS product, and it is a better education than most companies can offer.
The people-and-agents future is being built here, in production. We think humans and AI agents will share one system of action for work. We are building t Panchayat Bhavan oh my Godhat system now, for customers who already depend on it, and you will work on that problem directly whatever your role.
Your name is on the work. The teams are deeply connected enough that credit and responsibility both find you fast. That is some pressure. Mostly it is the fun part.
If that sounds like your kind of place, we would like to meet you.