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Lead AI Engineer (Python / LLM / Agentic AI)

Emaratech · Cairo

New
Senior 🇬🇧 English
Python FastAPI Pydantic LangChain LangGraph RAG Vector databases PostgreSQL Redis Docker REST API NATS Kafka MCP

Job description

About the role

Emaratech is looking for an experienced Lead AI Engineer in Cairo to design, develop and deliver production-ready AI applications and backend services. The ideal candidate combines strong Python backend engineering with hands-on experience building LLM-powered applications, AI agents and intelligent automation.

Key responsibilities

  • Design, develop and maintain scalable backend services and AI applications in Python
  • Build AI agents and agentic workflows, including tool calling, orchestration, multi-step reasoning and multi-agent collaboration
  • Develop LLM solutions using RAG, embeddings, vector databases and structured outputs
  • Integrate LLMs with internal systems, enterprise APIs and external services via MCP and other approaches
  • Evaluate and optimise AI solutions for accuracy, reliability, performance, latency and cost
  • Design scalable architectures with asynchronous processing, message queues, caching and event-driven patterns
  • Implement AI security controls such as prompt injection protection, data privacy, access control and safe tool execution
  • Build and deploy production services with testing, monitoring, logging and error handling
  • Collaborate with product and engineering teams, lead technical design, review code, mentor engineers and set engineering best practices

Required profile

  • 7+ years of professional software engineering experience, including at least 2 years of Python backend development
  • Hands-on experience deploying LLM-powered applications in production
  • Experience delivering major features or products from concept to production
  • Strong analytical, troubleshooting, communication and technical leadership skills

Required skills

  • Python, FastAPI, async programming, Pydantic
  • LLM integration, RAG, embeddings, vector databases (Qdrant, pgvector, Pinecone)
  • AI agents, tool/function calling, agent orchestration (LangGraph, LangChain, MCP)
  • PostgreSQL, Redis, Docker, REST APIs, NATS, Kafka
  • Automated testing, clean architecture, design patterns

Questions fréquentes

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Source : ats:workable

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Published 4 hours ago

Expires 1 month from now

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Emaratech

Cairo