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zaimler

AI readiness platform for enterprise data

Full Stack Engineer

Full-Stack EngineeringConfirmed live in the last 24 hours
Full-timeSan Mateo, CA, USAIn-person

About the Job

Requirements

  • You have shipped production software end to end and can point to something you built.
  • You are strong on the backend with Python, Go, Java, or a similar technology, and can build a real React and TypeScript application without waiting for a designer.
  • You have opinions about API design and data modeling and can defend them.
  • You have operated software in the cloud using AWS, Google Cloud Platform, or Microsoft Azure and debugged production issues.
  • You make pragmatic decisions under ambiguity and understand which tradeoffs are worth debating.
  • You want to work directly with customers.

Responsibilities

  • Ship features across the whole stack using React and TypeScript on the frontend, Python or Go underneath, and real data models between them.
  • Talk directly with customers, join calls, observe how they use the product, and ship improvements based on what you learn.
  • Work with platform, data, and machine learning engineers to determine system capabilities and design product experiences around them.
  • Take work from idea through production, including testing, deployments, monitoring, and subsequent iterations.
  • Improve the APIs, tooling, and user-interface patterns so the platform requires less explanation.
  • Own a major product surface and decide how it is built.
  • Raise the standard for how the team ships software.

Desired Qualifications

  • Experience with data-heavy or developer-facing products.
  • Experience with distributed systems.
  • Experience with machine-learning-adjacent platforms.
  • Experience with Kubernetes.
  • Experience with observability and performance work.
  • A genuine interest in artificial intelligence infrastructure.

About the Company

zaimler

AI readiness platform for enterprise data

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 enterprise data, automates taxonomy creation and knowledge-graph representations, and processes data at scale to prepare datasets for machine learning and business intelligence. Led by veterans from LinkedIn, Meta, and Visa, it targets large enterprises with a focus on automating taxonomies and knowledge graphs, backed by venture funding and early design partnerships in a B2B subscription model. Its goal is to become the standard platform that unlocks the value of enterprise data for AI-driven decision making.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Not listed
Founded
2024

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