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Embedded Infrastructure Engineer, Chanakya

Sarvam AIDelhiEngineering
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Salary
Not listed
Job type
Full-time
Posted
17 Apr 2026
Status
Open · checked 7d ago

About this role

Sarvam AI is seeking an Embedded Infrastructure Engineer to join their engineering team in Delhi on a full-time basis. This role suits an experienced data platform professional ready to design and manage critical infrastructure for large-scale AI deployments at client locations.

Role Overview

The Embedded Infrastructure Engineer designs, builds, and maintains the data infrastructure required for AI system deployments at client sites. Working closely with data scientists and deployment engineers, this position ensures that massive datasets can be securely ingested, stored, and served to AI reasoning engines. Professionals in this role will handle terabyte-scale persistent data stores and large daily ingestion volumes across diverse data types, including structured records, documents, imagery, audio, and geospatial data, often within air-gapped or restricted environments.

Key Responsibilities

Design and operate various data storage architectures, including relational, document, vector, and object storage, to handle multi-terabyte datasets.
Build and maintain reliable batch and streaming data ingestion pipelines featuring robust monitoring, error handling, and backpressure management.
Implement strategic indexing, partitioning, and query optimisation techniques to ensure fast data retrieval and low-latency reasoning for AI systems.
Collaborate with data scientists to translate semantic structures and ontologies into performant physical data models.
Deploy and manage search infrastructure, vector stores, and database systems in on-premise or security-constrained settings.
Implement comprehensive observability for the data platform to track pipeline health, query performance, storage utilisation, and ingestion lag.
Handle capacity planning and scaling choices for data infrastructure across assigned client accounts.
Partner with engineering teams to feed infrastructure insights back into core platform tooling.

Requirements

Possesses four to eight years of professional background in data engineering, data infrastructure, platform engineering, or site reliability engineering at significant data scale.
Demonstrates direct experience managing persistent multi-terabyte data stores handling 10TB+ of data and high-throughput ingestion.
Exhibits deep working knowledge of at least two systems among PostgreSQL, MongoDB, Elasticsearch, or ClickHouse, covering operational management, tuning, and indexing.
Brings experience creating production data ingestion frameworks using tools like Apache Kafka, Apache Spark, Airflow, or dbt.
Shows strong proficiency in Python and/or Go for writing production infrastructure automation and tooling.
Understands storage systems and formats thoroughly, including object storage and columnar formats.
Possesses familiarity with containerisation and orchestration using Docker and Kubernetes in production environments.
Demonstrates experience with infrastructure-as-code and deployment automation via Terraform or similar utilities.

Nice to Have

Practical experience utilising vector databases or embedding stores such as Milvus, Weaviate, Qdrant, or pgvector.
Prior background in deploying and operating infrastructure within hybrid, on-premise, or air-gapped environments.

Skills and Tools

Python
Go
Kubernetes
Docker
Apache Spark
Apache Kafka
Airflow
dbt
Terraform
PostgreSQL
MongoDB
Elasticsearch
ClickHouse

About the Company

Sarvam AI is developing India's full-stack sovereign AI platform, focusing on research, models, infrastructure, and applications to make artificial intelligence functional for the country. The company collaborates with prominent enterprises and public institutions, supported by investors including Lightspeed, Peak XV, and Khosla Ventures, alongside major brand partners like Tata Capital, SBI Life, CRED, IDFC, and LIC.

How to Apply

Interested candidates should visit the official Sarvam AI careers page to submit their application.

Skills and tech stack

PythonKubernetesDockerSparkKafkaAirflowdbtTerraform

Questions candidates ask

What is the primary focus of the Embedded Infrastructure Engineer role?

The role focuses on designing, building, and maintaining the data infrastructure that supports AI system deployments at client sites, ensuring terabyte-scale datasets are reliably ingested and stored.

Where is the position located?

The position is located in Delhi, India.

What level of experience is required for this role?

The company looks for candidates with 4 to 8 years of experience in data engineering, data infrastructure, platform engineering, or site reliability engineering.

What specific technical skills are mentioned in the requirements?

Required skills include Python or Go, containerisation with Docker and Kubernetes, infrastructure-as-code with Terraform, and experience with data tools like Spark, Kafka, Airflow, and various database systems.

How can I apply for this job?

Candidates can apply by visiting the official Sarvam AI careers website.

Ready to apply?

The application is on the official Sarvam AI careers page.

Apply on company site