Full-Time

Software Engineer

Distributed Systems

zaimler

zaimler

1-10 employees

AI readiness platform for enterprise data

No salary listed

H1B Sponsorship Available

San Mateo, CA, USA

In Person

Category
Software Engineering (1)
Required Skills
Rust
Java
C/C++
Linux/Unix
Requirements
  • Deep experience building distributed systems at scale: high queries per second environments, multi-region deployments, consistency and availability tradeoffs.
  • Fluency in Java, C++, or Rust; comfortable working at the systems level.
  • Strong grasp of consistency models, consensus protocols, and replication strategies.
  • Experience with traffic and data partitioning, network protocol design, and database internals.
  • Hands-on Linux systems, distributed file systems, OS internals.
  • Ability to build durable, observable, and operationally sound systems that hold up under real load.
Responsibilities
  • Design and build distributed storage and coordination systems from first principles, fault-tolerant, strongly consistent, and performant under high load.
  • Own consistency and availability tradeoffs at the data layer, implement and tune consensus protocols for production workloads.
  • Build and optimize query execution engines for knowledge graphs.
  • Architect data partitioning and replication strategies to meet throughput and durability service level agreements.
  • Work at the system level, tune input/output scheduling, network stacks, and memory management for distributed workloads.
  • Collaborate with machine learning and product engineers to ensure the data layer meets the latency, throughput, and consistency requirements of agentic artificial intelligence workloads.
  • Debug and harden distributed systems in production: resource contention, split-brain scenarios, cascading failures.
Desired Qualifications
  • Experience building or deeply understanding query engines (OLAP/OLTP), ingestion pipelines, or storage layers.
  • Kubernetes and cloud infrastructure (Amazon Web Services, Microsoft Azure, Google Cloud Platform) at production scale.
  • Prior work on knowledge graphs, graph databases, or semantic data layers.
  • Track record of shipping systems that other engineers depend on.

Zaimler builds an enterprise data platform that makes data AI-ready by simplifying and organizing complex datasets for advanced applications. The platform ingests and structures data, automates taxonomy creation and knowledge-graph representations, and enables scalable preparation for machine learning and business intelligence. Led by veterans from LinkedIn, Meta, and Visa, Zaimler targets large-scale enterprises with an emphasis on AI readiness and scalable data infrastructure, backed by venture funding and early design partnerships. Its goal is to become the standard platform that lets large organizations unlock the value of their data through AI-ready infrastructure and scalable AI applications.

Company Size

1-10

Company Stage

N/A

Total Funding

N/A

Headquarters

N/A

Founded

N/A

Simplify Jobs

Simplify's Take

What believers are saying

  • Series A funding accelerates scaling of context infrastructure for enterprise AI.
  • $10 trillion TAM in enterprise data preparation and AI readiness.
  • Strong design partner validation signals product-market fit in mid-market segment.

What critics are saying

  • 23 unfilled roles including MLEs delay product deployment versus better-staffed competitors.
  • Databricks Unity Catalog directly competes on ontology automation and data governance.
  • Lack of revenue visibility beyond design partners threatens runway sustainability.

What makes zaimler unique

  • Auto-inferred ontology enables semantic reasoning without manual taxonomy creation.
  • Founding team built knowledge graphs at LinkedIn, Facebook, and Visa.
  • Runtime context graph unifies fragmented enterprise data for AI applications.

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Benefits

Health Insurance

Flexible PTO

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