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описание
The client is an international technology company developing a modular software platform for complex business operations and automated workflows. Its teams build and implement scalable solutions across different environments and use cases.
задачи
Design, build, and ship backend services and automated workflows from initial requirements through production
Build reusable tools and integration services with clear schemas, validation, and interfaces
Integrate third-party APIs and internal services, handling authentication, retries, rate limits, and idempotency
Implement workflow orchestration, including state, execution limits, permissions, error handling, and human approval steps
Build and maintain MCP servers and other tool interfaces for model-driven applications
Develop and refine LLM instructions and tool descriptions so applications select appropriate actions and provide valid arguments
Configure model selection, reasoning settings, tool permissions, and execution limits for each workflow
Debug production failures, including incorrect tool selection, invalid arguments, missing actions, and incomplete execution
Package and deploy services with Docker to cloud runtimes, with logging and instrumentation for diagnosis
Add features and integrations to live services while protecting existing behavior through testing and regression checks
Take initiative on architecture and reliability, identify problems early, and propose practical improvements across system boundaries
Document services and explain their behavior to internal teams and, when needed, client engineers
требования
At least 3 years of production backend software development experience
Strong TypeScript and Node.js skills
Practical experience integrating REST APIs and third-party systems, including authentication, structured data, and failure handling
Docker skills and experience with at least one cloud platform: AWS, GCP, or Azure
Hands-on experience building LLM applications that call tools, using an established SDK or framework or a custom execution loop
Practical experience with MCP or equivalent tool-integration patterns
Established habits around Git, automated testing, code review, and debugging production software
Ability to make technical decisions independently, take ownership of outcomes, and communicate clearly in written English
A degree in Computer Science or equivalent practical experience
Будет плюсом: production experience with Claude Agent SDK, the Anthropic or OpenAI APIs, LangChain/LangGraph, or Vercel AI SDK; experience writing MCP servers and evaluating model output with test sets, regression checks, or evaluation frameworks; hands-on AWS experience with ECS/Fargate, Lambda, IAM, or DynamoDB; experience integrating customer service platforms such as Gladly, Zendesk, Salesforce, or Amazon Connect; Python for data work
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