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India
Remote only
Every month, 2.6 billion messages flow through our platform. Our automation engine enrolls 3.1 billion contacts and executes 21.5 billion workflow actions in the same window — with API traffic peaking at 28,000+ requests per second. Booking appointments, closing deals, answering customers. If these systems lag, businesses lose leads. If they go down, people lose income.
We're hiring backend engineers who treat that as a design constraint, not a fun fact.
This isn't a role where you'll implement someone else's spec. You'll be handed problems that don't have a known answer yet — a datastore buckling under index growth, a queue that needs to absorb 10x burst traffic without dropping a message, a state machine with millions of concurrent executions. You'll figure it out. And you'll own it.
Design and build Node.js / Go services on critical paths — high throughput, low latency, zero tolerance for data loss
Own systems end to end: architecture, design docs, code, tests, rollout, and production health
Model and optimize data layers across SQL and NoSQL stores handling high read/write volumes and atomic updates
Build queueing, caching, and rate-limiting layers that keep the platform graceful under burst traffic
Instrument everything — logs, metrics, traces — so you know your system is healthy before anyone asks
Debug production incidents, ship the fix, drive the post-mortem to closure
Review code, raise the bar, and pull the engineers around you up with you.
4+ years of backend engineering experience, with deep hands-on work in Node.js and/or Go
Queueing experience — you've designed with Pub/Sub, Kafka, RabbitMQ, Cloud Tasks, or similar, and you understand delivery semantics, ordering, and backpressure
Complex distributed systems experience — consistency trade-offs, idempotency, fault tolerance, systems that stay correct under partial failure
Hands-on with Redis or other in-memory data stores — caching strategies, data structures, and their failure modes
Strong with SQL or NoSQL databases — schema design, indexing, and query optimization at high volume
You write clear design docs and rigorous test cases as a habit, not on request
Champion of AI-assisted engineering — you make agents produce accurate, production-quality code, fast
Languages: Node.js (TypeScript), Go
Storage: MongoDB, Firestore, Redis, ElasticSearch, ClickHouse
Infra: GCP — GKE, Pub/Sub, Cloud Tasks
CI/CD: GitHub Actions, Docker, Kubernetes
We're past the debate. AI is part of how we build — and we expect you to be better at it than most.
That means making agents do real work: producing code that's accurate, tested, and slop-free — fast. You know when to hand a problem to an agent and when to take the wheel. You review AI output with the same rigor as a junior engineer's PR, and you ship at a pace that engineers without this skill can't match.
If you're still copy-pasting from a chat window and hoping, this isn't the seat for you.
You've solved problems nobody handed you a playbook for — ideally in a 0→1 environment where the system didn't exist until you built it
You understand systems in depth — not just the API surface, but what happens under load, at the tail, when the network partitions
You write design docs people actually read — clear trade-offs, honest risks, a real recommendation
You treat test cases as part of the design, not a chore after the fact
When production breaks at 2 AM, your first instinct is curiosity, not panic
Familiarity with our stack: GCP, MongoDB, Firestore, ClickHouse, ElasticSearch
You've built or scaled messaging, automation, or event-driven platforms
You've taken a system from 0→1, or rebuilt one mid-flight without breaking it
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