Zaimler8mo ago

Full Stack Engineer

United States·San MateoFull Timemid

EngineeringOtherFullstack Developer

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Quick Summary

Overview

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.

Technical Tools

awsazuregcpgojavakubernetespythonreacttypescriptapi-designdatabase-designdistributed-systemsperformance-optimization

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.

Our platform is used by engineers, and engineers judge infrastructure by how fast it stops confusing them.

We have a hard system underneath: graphs, real-time inference, agent behavior in production. Today, understanding it takes a conversation with us. That's a ceiling on how fast we grow. This role exists to remove it, by owning the surface where customers actually meet the product and making it obvious.

You'll own product surface end to end: the interfaces, the APIs behind them, and the data models underneath.

The hard part isn't the CRUD. It's making genuinely complex system behavior legible and fast for the people using it. That takes taste as much as it takes engineering.

The split is roughly [60% frontend and API layer, 40% backend services]. You will not be handed a design file, and you will not be handed a spec. If you want to go deep on distributed systems and never touch a UI, this is the wrong role. If you can't hold your own on the backend either, it's also the wrong role.

We're small and senior. You'll pick the architecture, ship it, watch it in production, and fix what's wrong.

Ship features across the whole stack. React and TypeScript on top, Python or Go underneath, real data models in between

Talk to customers directly. Join calls, watch people use what you built, and ship against what you learn

Sit with platform, data, and ML engineers to figure out what the system can do, then design a product experience around it

Take things from idea to production, including the testing, deploys, monitoring, and the second version after you learn you got it wrong

Sharpen the APIs, tooling, and UI patterns so the platform stops needing explanation

First few weeks: You've shipped something real to production and sat in on a customer call

First few months: You own a major surface of the product outright, and you're the person who decides how it's built

Beyond: The platform is noticeably easier to understand than when you arrived, and you're raising the bar on how everyone here ships

We care about what you've built, not how long you've been building.

You've shipped production software end to end and can point at something and say "I built that"

You're strong on the backend (Python, Go, Java, or similar) and can build a real React/TypeScript app without waiting for a designer

You have opinions about API design and data modeling, and can defend them

You've operated things in the cloud (AWS, GCP, or Azure) and debugged them at 11pm

You make pragmatic calls under ambiguity and know which tradeoffs are worth the argument

You want to be near customers, not shielded from them

Helps, doesn't gate: data-heavy or developer-facing products, distributed systems, ML-adjacent platforms, Kubernetes, observability and performance work, a real interest in AI infrastructure.

Meaningful equity. You're early. The scope and the upside both reflect that.

The infrastructure layer for agentic AI is being built right now. Very few people get to work on a layer this foundational this early.

Small, senior team. Your scope is as large as you're willing to make it.

Real ownership of both architecture and product direction, not a ticket queue.

Full benefits (medical, dental, vision, 401k). We sponsor H-1B visas and help with immigration.

Send us (what you've built: a repo, a product, a thing you shipped that you're proud of) at caleb@zaimler.ai. Tell us what was hard about it.

We value builders over résumés. If this role excites you but you don't check every box, apply anyway and show us the work.

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.