Visit us: risicare.ai
Drop your CV: [email protected], [email protected]

Observability Platform Engineer

Role: Backend + Data Infrastructure + AWS/DevOps
Experience: 2-5 years
Location: Remote / (Hybrid - Bangalore / Delhi)
Compensation: INR 12 LPA - 20 LPA + ESOP*

Read this part firstWe're building an observability platform for teams running LLMs in production - traces, spans, token cost, latency, eval scores. The stuff that tells you why your AI application did what it did, instead of leaving you to guess from logs.
We are pre-launch. Zero paying customers today. The pipeline is built and hardened; the product surface is not. That's the honest state of things, and it's the most important thing to know before you read further.
You'd be the first engineering hire. Founder plus you.
If "no customers yet, first engineer, you'll own the platform" reads as a risk to avoid, this isn't your role, and there's no hard feelings in that. If it reads as the interesting part, keep going.

What you'd actually ownYou own the platform end to end. Not a service within it. The platform.




The ingestion path. Customer SDKs send us spans. A Rust gateway takes them, Redis buffers them, ClickHouse stores them. Every stage of that has to hold up when things go wrong – because "we dropped your traces" is the one failure an observability vendor doesn't get to have.
The query path. ClickHouse, holding span data that has to stay quick as it grows. High-cardinality queries over a lot of rows. This is where the product either feels good or doesn't.
The control plane. Python/FastAPI over Postgres - organisations, projects, API keys, roles and permissions, audit logging. Multi-tenant, so the isolation has to be genuinely correct rather than approximately correct.
The dashboard. Next.js/TypeScript. Where customers actually see their traces.
The infrastructure. AWS. Deploys, IaC, CI/CD, cost, uptime.
Some weeks you're tuning a ClickHouse query. Some weeks you're in Terraform. Some weeks you're

📌 Observability Platform Engineer (India)
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