Embedded Infrastructure Engineer, Chanakya

Highlights

• Design data infrastructure underpinning AI deployments at client sites.
• Manage terabyte-scale datasets across documents, imagery, audio and geospatial.
• Operate reliable data platforms in air-gapped, constrained environments.

Ideal candidate

An ownership-driven infrastructure builder who thrives in constrained field environments and cares about reliable, performant data systems powering real-world AI impact at population scale.

Requirements

• 4-8 years in data infrastructure, data engineering, platform engineering or SRE at significant data scale
• Direct experience building or operating 10TB+ persistent data stores with high-throughput ingestion
• Deep working knowledge of at least two of: PostgreSQL, MongoDB, Elasticsearch, ClickHouse or comparable
• Experience building production ingestion pipelines using Kafka, Spark, Airflow, Flink, dbt or equivalent
• Strong proficiency in Python and/or Go for production infrastructure tooling and automation
• Understanding of object storage (S3/MinIO) and columnar formats (Parquet, ORC)
• Familiarity with Docker and Kubernetes in production settings
• Experience with infrastructure-as-code and deployment automation like Terraform