Description
Software Engineer, Distributed Systems
Team: Infrastructure
Location: San Mateo, CA
Commitment: Full Time
Workplace Type: onsite
About zaimler
AI agents can't reason over data they don't understand. Enterprise data today is fragmented across dozens of systems with no shared context, meaning, or structure, and that's why most enterprise AI is failing. The shift from copilots to autonomous agents is creating an entirely new infrastructure layer, and we're building it.
zaimler is the context infrastructure for the agentic era: a platform that automatically discovers domain knowledge, maps relationships, and gives AI agents the semantic understanding to operate with precision at scale. Imagine knowledge graphs that support real-time inference, built for systems that need to reason, not just retrieve.
zaimler was founded by Biswajit Das (ex-VP Engineering, Truera), a Data Infra veteran and former Chief Architect at Visa, and Sofus Macskassy (ex-Director of Engineering, LinkedIn), who built one of the largest knowledge graphs in production in the industry at LinkedIn. We're growing and deploying with major enterprises across insurance, travel, and technology. If you want to build infrastructure that the next decade of enterprise AI runs on, we'd love to talk.
The Role
We’re looking for a Software Engineer, Distributed Systems to own the core infrastructure layer that makes our semantic platform fast, durable, and scalable. You’ll be building primitives: storage engines, consistency protocols, query execution layers, and coordination services that operate reliably at scale.
What You’ll Do
- 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 SLAs.
- Work at the system level, tune I/O scheduling, network stacks, and memory management for distributed workloads.
- Collaborate with ML and product engineers to ensure the data layer meets the latency, throughput, and consistency requirements of agentic AI workloads.
- Debug and harden distributed systems in production: resource contention, split-brain scenarios, cascading failures.
What We’re Looking For
- Deep experience building distributed systems at scale: high QPS 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.
Strong Pluses
- Experience building or deeply understanding query engines (OLAP/OLTP), ingestion pipelines, or storage layers.
- Kubernetes and cloud infrastructure (AWS, Azure, GCP) at production scale.
- Prior work on knowledge graphs, graph databases, or semantic data layers.
- Track record of shipping systems that other engineers depend on.
Why Join
- A rare chance to be a founding engineer shaping both company and product direction.
- Competitive salary, benefits, and meaningful equity.
- Work alongside engineers and researchers from LinkedIn, Visa, Meta, and Branch.
- Onsite culture in San Mateo, designed for deep collaboration and high-velocity building.
- Full benefits package (Medical, Dental, Vision, 401k).
- We transfer H-1B visas and assist with immigration processes.
We value builders over résumés. If this role excites you but you don't check every box, we still want to hear from you. zaimler is an equal opportunity employer.
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