Data Infrastructure Engineer

About zaimler

zaimler is building the semantic platform that links fragmented enterprise data and extracts meaning with knowledge-distilled models. We’re creating the foundation for AI systems that don’t just generate, but retrieve, link, and reason over enterprise knowledge.

In just over a year, we’ve begun partnering with Fortune 500 design partners in insurance, travel, and technology, deploying semantic AI infrastructure into some of the world’s most complex data ecosystems. Our platform enables enterprises to make data AI-ready from the start : automating ontology creation, data mapping, and retrieval-augmented reasoning at scale.

Our team comes from LinkedIn, Visa, Meta, and Branch, and has spent decades solving data and infrastructure challenges at scale. Backed by top VCs, we’re building the next foundational layer for enterprise AI.

The Role

We’re looking for a Data Infrastructure Engineer to build the foundational distributed data layer that feeds our semantic platform. You’ll design, build, and scale systems for high-throughput data ingestion, transformation, and real-time processing.

What You’ll Do

• Build and operate large-scale data pipelines on Spark, Kafka, and Ray.
• Design fault-tolerant streaming and batch systems that move terabytes reliably.
• Optimize data workflows for performance, cost, and latency.
• Collaborate with ML and product engineers to ensure data is discoverable, structured, and queryable.
• Automate deployments with Kubernetes, Terraform, and CI / CD pipelines.
• Monitor, debug, and improve distributed jobs in production.

What We’re Looking For

Why Join