Lead - Artificial Intelligence Engineer
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Before you apply
LocationCairo, Cairo Governorate, Egypt
Typefull-time
SeniorityLead
Experience7+ yrs
Departmentemaratech G
Company size201–500 people
PostedOct 26, 2026 · 1w ago
Verified live3d ago
At a glanceSummarised by Seekless from the posting.
7+ years of professional software engineering experience, including at least 2 years of backend development using Python
Strong experience with Python, FastAPI, asynchronous programming, and Pydantic
Hands-on experience developing and deploying LLM-powered applications in production
Practical experience with AI agents, tool/function calling, and agent orchestration frameworks, such as LangGraph, LangChain, or equivalent solutions
Strong understanding of RAG architectures, embeddings, semantic search, and vector databases
Experience integrating LLMs through APIs, including structured outputs, prompt engineering, and handling model failures
Experience evaluating LLM applications, including response quality, hallucinations, reliability, and performance
Solid understanding of distributed systems, message queues, caching, retries, idempotency, and persistent state management
Experience with PostgreSQL, Redis, Docker, and REST APIs
Strong knowledge of automated testing, clean architecture, design patterns, and code quality practices
Experience designing and delivering major features or products from concept to production
Strong analytical, troubleshooting, communication, and technical leadership skills
Experience with Model Context Protocol (MCP) and building MCP servers or clients
Experience with advanced agent orchestration, multi-agent architectures, and human-in-the-loop workflows
Experience with Qdrant, pgvector, Pinecone, or similar vector databases
Experience with NATS, Kafka, or other event-driven messaging technologies
Skills
Python
FastAPI
Pydantic
LangGraph
LangChain
RAG
MCP
PostgreSQL
Redis
Docker
REST APIs
Qdrant
pgvector
Pinecone
NATS
Kafka
Lead AI Engineer (Python / LLM / Agentic AI)
Job Description
We are looking for an experienced Lead AI Engineer to design, develop, and deliver production-ready AI applications and backend services.
The ideal candidate combines strong Python backend engineering skills with hands-on experience building LLM-powered applications, AI agents, and intelligent automation solutions.
Key Responsibilities
•
Design, develop, and maintain scalable backend services and AI-powered applications using Python.
•
Design and implement AI agents and agentic workflows, including tool calling, orchestration, multi-step reasoning, and multi-agent collaboration.
•
Build LLM-powered solutions using RAG, embeddings, vector databases, and structured outputs.
•
Integrate LLMs with internal systems, enterprise APIs, and external services using MCP and other integration approaches.
•
Evaluate and optimize AI solutions for accuracy, reliability, performance, latency, and cost.
•
Design scalable architectures using asynchronous processing, message queues, caching, and event-driven patterns.
•
Implement AI security controls, including prompt injection protection, data privacy, access control, and safe tool execution.
•
Build and deploy production-ready services with proper testing, monitoring, logging, and error handling.
•
Collaborate with product and engineering teams to translate business requirements into technical solutions.
•
Lead technical design discussions, review code, mentor engineers, and establish engineering best practices.
Requirements
Job Requirements
Required Qualifications
•
7+ years of professional software engineering experience, including at least 2 years of backend development using Python.
•
Strong experience with Python, FastAPI, asynchronous programming, and Pydantic.
•
Hands-on experience developing and deploying LLM-powered applications in production.
•
Practical experience with AI agents, tool/function calling, and agent orchestration frameworks, such as LangGraph, LangChain, or equivalent solutions.
•
Strong understanding of RAG architectures, embeddings, semantic search, and vector databases.
•
Experience integrating LLMs through APIs, including structured outputs, prompt engineering, and handling model failures.
•
Experience evaluating LLM applications, including response quality, hallucinations, reliability, and performance.
•
Solid understanding of distributed systems, message queues, caching, retries, idempotency, and persistent state management.
•
Experience with PostgreSQL, Redis, Docker, and REST APIs.
•
Strong knowledge of automated testing, clean architecture, design patterns, and code quality practices.
•
Experience designing and delivering major features or products from concept to production.
•
Strong analytical, troubleshooting, communication, and technical leadership skills.
•
Experience with Model Context Protocol (MCP) and building MCP servers or clients.
•
Experience with advanced agent orchestration, multi-agent architectures, and human-in-the-loop workflows.
•
Experience with Qdrant, pgvector, Pinecone, or similar vector databases.
•
Experience with NATS, Kafka, or other event-driven messaging technologies.