Cloud Infrastructure Engineer

About the role

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.

What You’ll Do

As our Founding Cloud Infrastructure Engineer, you’ll design, build, and own the cloud infrastructure that powers zaimler’s semantic platform. This isn’t a maintenance role. It’s a foundational build-from-scratch position, shaping choices we’ll live with for years.

Key Responsibilities - Architect & Scale Infra: Design and deploy secure, fault-tolerant cloud infrastructure across AWS/Azure/GCP, using Kubernetes, Terraform, and modern IaC tools.

- Enable Distributed AI Workloads: Build and optimize compute systems for distributed frameworks like Ray and Kafka, ensuring scalability and reliability.

- GPU Orchestration: Manage GPU resources and scheduling for ML inference, retrieval, and training workloads.

- Drive Observability & Reliability: Implement monitoring, security, and best practices for high-availability ML/AI systems.

- Collaborate Across Teams: Work hand-in-hand with ML researchers and data scientists to ensure infra accelerates, not hinders, development.

Who We’re Looking For - We’re open to multiple levels of seniority (3–10+ years of engineering experience). What matters most is founder mindset + strong infra chops.

- Hands-on with Kubernetes + Terraform (real-world deployments, not just exposure).

- Experience with distributed systems (Ray, Dask, Spark, or similar).

- Exposure to Kafka or equivalent MQ systems.

- Strong programming/scripting in Python, Go, or similar.

- Track record of building or operating production-grade infra.

Nice to Haves - GPU scheduling/optimization experience.

- Prior startup/early-stage build-from-scratch experience.

- Experience supporting ML/AI workloads in production.

- Founder Traits