Senior Software Engineer (Dapr OSS) – India Lead
Diagrid, Remote India +1
The role
You join Diagrid's Runtime team, the engineers who build Dapr and run it inside Diagrid Catalyst. Your work lands in public, in the Dapr open source project, and in the product our customers run in production.
You will design and ship features in the Dapr runtime, review code from the community and from your team, and help keep releases stable. Much of the current work is in durable execution (Dapr Workflows, actors and the scheduler), where correctness under failure matters more than speed.
We build with AI every day. We look for engineers who use AI to go further and who check what it produces: you read the diff, you test the failure path, and you own the result, whoever or whatever wrote the first draft. In an open source project, reviewing and verifying code matters as much as writing it.
You are a full member of the team: the same ownership, the same voice in design, and the same chance to grow into a Dapr maintainer as everyone else.
Working hours
Diagrid's team works across Europe and North America.
Our India team’s day typically starts around 12:00 PM IST, with afternoons overlapping Europe and evenings overlapping the US. You’ll need to be available for a core US overlap window of 8:30 PM to 12:00 AM IST; outside that, you can structure your day flexibly.
What you will do
- Design and build features in the Dapr runtime, from proposal to release.
- Review pull requests from the community and from your team. Hold the bar on correctness, tests and API design.
- Find and fix bugs in distributed code: race conditions, retries, partial failures, and state that must survive a crash.
- Write proposals and design docs in public, and respond to review on them.
- Take part in Dapr releases: release candidates, patch releases and security fixes.
- Help users and contributors on GitHub and Discord, and mentor new contributors.
What you need
- 5+ years of professional Go, with production code you can explain line by line.
- Experience designing and running distributed systems. You know how they fail, and you design for it.
- 2+ years with Kubernetes and containers.
- A strong computer science base: concurrency, networking and data consistency.
- Daily, practical use of AI coding tools, and the judgment to check their output before you ship it.
- Clear written English. Most of our work happens in GitHub issues, pull requests and design docs, read by people across many companies and time zones.