Platform Engineer

Responsibilities

• Build and scale shared backend systems including the AI engine, workflow runtimes, and integration layers
• Design clear APIs, data models, and abstractions that allow other engineers to build features reliably
• Manage core platform components such as document processing, authentication, billing, and queues
• Optimize context-window usage and handle model-provider failures during streaming responses
• Develop secure code execution services and flexible integration layers for external services
• Ensure system reliability through testing, observability, and handling complex failure modes

Requirements

• 3 to 6 years of experience building backend systems that handle real load (queues, caches, databases, streaming pipelines)
• Strong proficiency in TypeScript and Node.js
• Experience with infrastructure tools such as Terraform and Kubernetes
• Technical knowledge of the LLM ecosystem, including context windows, tool calling, and streaming protocols
• A security-first mindset with a focus on multi-tenant data isolation
• Experience with observability tools like Datadog or Sentry to implement metrics, traces, and logs

Preferred Qualifications

• Experience working with multi-cloud environments (AWS, Azure, or GCP)
• Familiarity with the Model Context Protocol (MCP) or agent-to-agent communication
• Proficiency using AI-assisted development tools to increase engineering output

About the Company

Langdock provides a secure, model-agnostic platform that brings leading AI models to entire organizations. With over 6,000 companies using the platform, Langdock helps employees automate workflows, analyze documents, and work smarter by bridging the gap between AI technology and practical business application.