SDE2 - API Platform

About the Role

Sarvam's model APIs (LLM, ASR, TTS, Vision, Translate) are how developers and enterprises ship products on our foundation models. Our OpenAI-compatible LLM APIs route every request across multiple model deployments, with streaming, failover, metering, billing, and rate-limiting all part of the same stack. Today it's FastAPI and Python; we're in the middle of rewriting it in Go.

We're hiring a Software Engineer (SDE 2) to own core parts of this platform. The features. The reliability. The performance. This is an IC role.

What You'll Do

• Building and evolving the LLM API platform, from the moment a request hits the edge to the response that goes back out
• The Python→Go rewrite: building services in Go alongside the existing Python stack, without compromising reliability
• Streaming infrastructure: SSE for Chat Completions and Responses, long-lived connections, clean handling of cancellations and client disconnects
• Routing and failover: weighted provider chains, retries with backoff, and latency-driven admission control across model deployments
• Protocol compatibility: keeping the API faithful to the OpenAI spec across inference servers (vLLM, SGLang, Dynamo) that each behave slightly differently
• The commercial layer: metering, billing, and rate-limiting, engineered to the same bar as the model APIs themselves
• Performance and reliability for a multi-tenant platform serving long-context agentic and coding workloads
• Observability (logging, metrics, tracing), so the team can debug production confidently and quickly
• Integration and load testing: the harness that lets us ship fast without breaking customer-facing APIs
• Close partnership with the Inference and MLOps teams on production readiness for new model launches
• Design-first, documentation-first engineering culture within the team: RFCs before code, decisions written down, no tribal knowledge

What We're Looking For

• 3+ years building production backend systems
• Strong Python in production: asyncio, FastAPI or similar, and services you've built and operated under real load
• Working knowledge of Go, or a strong willingness to learn it: you'll work in both languages through the rewrite
• Experience building low-latency, multi-tenant backend services
• Hands-on experience with streaming systems: SSE or WebSockets, long-lived connections, backpressure
• Strong PostgreSQL and Redis fundamentals: schema design, query performance, caching, and rate limiting
• Comfort running services on Kubernetes in production
• An ownership mindset: you test before you ship, debug production with metrics, logs, and traces, and write the RCA afterwards

Bonus Points

• Experience serving or integrating LLMs in production, especially OpenAI-compatible APIs
• Familiarity with inference servers (vLLM, SGLang, Dynamo) and latency metrics such as time to first token and inter-token latency
• Experience building metering, billing, or usage-based pricing infrastructure
• Time at an early- or growth-stage startup: comfort with ambiguity, speed, and ownership