Full Stack developer; AI

Looking for strong Full Stack Engineers with hands-on experience in Angular-based frontend development and a solid understanding of AI-driven systems and MCP-based architectures to work on a scalable LLM-powered conversational platform
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This role is ideal for engineers who have hands on experience in building end-to-end systems from real-time conversational UIs to distributed backend services integrating LLMs and agent frameworks.

• Build and maintain LLM driven enterprise level applications in real production environment.
• Design and develop MCP tools using Python, FastAPI, or similar frameworks.
• Maintain multiple MCP services and LLM integrations.
• Develop Angular-based conversational user interfaces with real-time updates.
• Design scalable architectures capable of supporting high concurrency
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• Implement monitoring, logging, and tracing for AI workflows
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• Continuously optimize latency, cost, and response quality.
• Implement and support multi-agent architectures with context sharing and orchestration.
• Implement Web Socket-based communication for streaming AI responses.
• Use Redis for caching, session management, and conversation memory.
• Maintain scalable services for conversation state, workflow, and memory handling.
• Strong understanding of API contracts and schema-driven development.
• Understanding of Prompt engineering, Structured outputs, Tool calling patterns, Model limitations and failure modes.
• Good understanding of Agent orchestration patterns, Role-based agents, Task decomposition, Coordination and fallback mechanisms.

• Frontend:
  • Angular / React
  • RxJS and reactive programming
  • Real-time UI updates using Web Sockets
• Backend:
  • Python
  • FastAPI / async services
  • API and middleware development
• AI & Platform:
  • LLM integrations and tool calling
  • MCP / FastMCP
  • Lang Chain, Lang Graph
  • Multi-agent architectures
• Systems & Infrastructure:
  • Distributed systems and scalability concepts
  • Web Sockets, event-driven systems
  • Redis (caching, session, memory)
  • Databases:
    Cosmos DB, MongoDB
  • Vector databases:
    Pinecone or similar
• Cloud & Dev Ops:
  • Azure
    , Azure AI Foundry
  • Azure Git Hub (PRs, branching, CI/CD pipelines)