Senior Software Engineer - Data Infrastructure

present of AI; Bengaluru; Teletrabalho; INR 4 500 000 - 6 500 000; Tempo integral

Resumo da oferta

Sarvam AI seeks a Senior Software Engineer to own a shared data platform end to end, from event ingestion to the analytics warehouse and pipelines. The role requires hands-on production experience with columnar stores or event streaming, plus Go or Python, and building or running real pipelines or multi-tenant data services.

Comfort with AWS, Kubernetes and Terraform, along with a habit of testing, monitoring, and incident analysis, is essential to thrive in this on-call role at Bengaluru-based

Qualificações

• Hands-on production experience with a columnar store or event streaming.
• Proficiency in Go or Python.
• Built or run at least one real pipeline, transformation layer or multi-tenant data service.

Responsabilidades

• Own a shared data platform end to end, including event ingestion, analytical warehouse and pipelines.
• Manage production on-call, testing, debugging with metrics and incident write-ups.

Conhecimentos

Columnar store

Event streaming

Go

Python

Kafka

ClickHouse

OLAP databases

Terraform

Kubernetes

Incident response

RCAs

Ferramentas

Terraform

Kubernetes

Descrição da oferta de emprego

Senior Software Engineer - Data Infrastructure

Engineering · Bengaluru · FullTime · Senior level

This role owns a shared data platform end to end: the event ingestion path, the analytical warehouse, pipelines, access control and running it all in production on call. A strong candidate has hands on production experience with a columnar store or event streaming, plus Go or Python, and has built or run at least one real pipeline, transformation layer or multi tenant data service. Comfort with AWS, Kubernetes and Terraform, and a habit of testing, debugging with metrics and writing up incidents, matters more than breadth.

How it fits the AI era

The platform carries model traces, evals and billing data, so the work sits close to AI products without being model work itself. AI tools speed up writing pipelines and queries, but the judgment about schema design, isolation, cost and safe re-runs stays with the engineer. Reliability and clear ownership of shared data remain human responsibilities.

How it builds AI experience

Working here means handling the data that AI products emit, including traces and eval outputs, and possibly LLM observability tooling. That builds practical skill in observability and eval pipelines on top of core data engineering. Building it starts with solid streaming and warehouse fundamentals, then adding tracing and eval pipeline experience.

Worth showing

• ClickHouse or OLAP databases
• Kafka and event streaming
• Go or Python
• Terraform and Kubernetes
• Incident response and RCAs

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Sarvam AI

Sarvam AI builds a full-stack sovereign AI platform for Indian languages, developed, deployed, and governed entirely in India (per the company).