• Design, build, and maintain MCP servers and MCP-based integrations • Implement MCP tools, resources, prompts, and backend interfaces • Build reliable communication between AI agents, tools, and backend systems • Define clean contracts for MCP tools and services • Improve the stability, predictability, and maintainability of MCP infrastructure • Test MCP tool behavior across different usage scenarios • Monitor and improve the quality of AI-tool interactions • Build and maintain backend services using TypeScript and Node.js • Work with backend frameworks such as Hono, Fastify, NestJS, and Next.js backend/API routes • Implement REST APIs, internal endpoints, service-to-service integrations, and automation flows • Work with authentication, request validation, error handling, logging, and observability • Design clean, maintainable backend architecture for internal and production-facing systems • Write production-quality code with clear structure and good error handling • Build and deploy backend services on Cloudflare Workers • Work with edge runtime limitations and best practices • Design lightweight, performant services for edge/serverless environments • Debug issues related to worker execution, routing, request handling, and deployment • Use Cloudflare services when needed, such as KV, Durable Objects, Queues, R2, or D1 • Optimize backend services for performance, reliability, and cost efficiency • Build AI-powered workflows and internal automation tools • Design prompts, system instructions, and tool definitions for reliable AI behavior • Improve the quality, consistency, and predictability of AI outputs • Analyze AI workflow failures and improve prompts, context, or tool contracts • Structure data and context for better LLM performance • Build testable AI workflows that can be evaluated and improved over time • Work with LLM APIs such as OpenAI, Anthropic, Claude, or similar providers • Build integrations between internal systems, APIs, and AI tools • Automate repetitive operational or engineering workflows • Design backend flows that connect AI agents with real business systems • Ensure integrations are secure, observable, and maintainable • Build internal utilities and developer tools when needed • Investigate and fix issues across MCP servers, backend services, Cloudflare Workers, AI workflows, and API integrations • Improve logging, monitoring, and observability for AI/backend systems • Identify root causes of unreliable tool behavior or incorrect AI outputs • Make systems easier to debug, test, and maintain • Document technical decisions and implementation details clearly