{"id":3947778,"url":"https://alion.io/job/wuzzuf-ai-engineer","title":"AI Engineer","company":{"id":57497,"name":"WUZZUF","domain":"wuzzuf.net","url":"https://alion.io/company/wuzzuf","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":true,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Cairo, Egypt"],"countries":["EG"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":50000,"max":60000,"currency":"EGP","period":"month","gross":true,"usd_annual":13332},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"ASP.NET Core","optional":false},{"name":"Azure","optional":false},{"name":"C#","optional":false},{"name":"Clean Architecture","optional":false},{"name":"Context Engineering","optional":false},{"name":"Dependency Injection","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Search","optional":false},{"name":"SQL","optional":false},{"name":"CI/CD","optional":true},{"name":"Docker","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"Ollama","optional":true},{"name":"OpenTelemetry","optional":true},{"name":"pgvector","optional":true},{"name":"Pinecone","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Qdrant","optional":true},{"name":"Redis","optional":true},{"name":"Semantic Kernel","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-11-08T22:40:00Z","employer_posted_date":null,"last_verified_at":"2026-11-08T22:40:00Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"We are looking for a skilled AI Engineer with a strong background in .NET backend development and AI-Native Software Architecture to design, develop, and integrate intelligent capabilities into enterprise applications.\nThe ideal candidate should understand how to build the complete software architecture surrounding Large Language Models (LLMs), transforming AI models into secure, scalable, observable, and production-ready business solutions.\nThis role is not focused on training AI models from scratch. Instead, it focuses on LLM integration, AI orchestration, context engineering, retrieval, memory, guardrails, and building robust .NET services around AI models.\n\nKey Responsibilities\nDesign and implement AI-Native Software Architecture using C#, ASP.NET Core, and .NET.\n\nBuild modular AI application layers integrating LLMs with enterprise systems.\n\nDevelop AI orchestration services, prompt management, context engineering, and conversation memory components.\n\nImplement Retrieval-Augmented Generation (RAG) solutions using vector databases, embeddings, and semantic search.\n\nBuild AI agents capable of tool calling, function execution, and integration with internal business APIs.\n\nDevelop secure API layers connecting LLM providers such as OpenAI, Azure OpenAI, and other hosted or local models.\n\nImplement AI guardrails, input/output validation, access controls, and responsible AI mechanisms.\n\nDesign observability and monitoring capabilities for AI requests, token usage, latency, cost, and model performance.\n\nBuild AI evaluation and testing mechanisms to assess response quality, accuracy, and reliability.\n\nIntegrate AI services with existing enterprise applications, databases, and business workflows.\n\nApply clean architecture, SOLID principles, and modern software engineering practices.\n\nCollaborate with software architects, backend developers, and product teams to deliver production-ready AI solutions.\n\nRequirements\nMust-Have Skills\n3+ years of professional software development experience, with strong hands-on experience in C# and ASP.NET Core.\n\nSolid understanding of Clean Architecture, layered architecture, REST APIs, dependency injection, and microservices.\n\nPractical experience integrating LLMs through APIs such as OpenAI or Azure OpenAI.\n\nUnderstanding of AI-Native Architecture and the software components surrounding LLMs.\n\nExperience with prompt engineering, context management, and structured LLM outputs.\n\nKnowledge of RAG, embeddings, vector search, and document retrieval.\n\nFamiliarity with AI agents, function calling, and tool integration.\n\nStrong knowledge of SQL Server and database integration.\n\nUnderstanding of authentication, authorization, API security, and secure AI integration.\n\nExperience with Git and modern development workflows.\n\nPreferred / Nice-to-Have Skills\nMicrosoft Semantic Kernel, Microsoft Agent Framework, or similar AI orchestration frameworks.\n\nLangChain, LangGraph, or comparable agent frameworks.\n\nAzure AI Foundry and Azure AI Search.\n\nVector databases such as Qdrant, Pinecone, Weaviate, or PostgreSQL with pgvector.\n\nModel Context Protocol (MCP).\n\nMulti-agent orchestration and agent workflows.\n\nAI evaluation frameworks, tracing, and OpenTelemetry.\n\nRedis for caching and conversation memory.\n\nDocker, CI/CD, and cloud deployment.\n\nExperience with local LLMs using Ollama or similar technologies.\n\nKnowledge of AI security, prompt injection prevention, and data privacy.\n\nWhat We're Looking For\nWe are particularly interested in engineers who understand that building an AI application is much more than sending a prompt to an LLM API.\nYou should be able to architect and implement the software layers that make AI reliable, secure, maintainable, and useful within real enterprise applications.\nAn ideal candidate can take an existing .NET business application and transform it into an AI-Native application by designing and implementing the required AI integration, orchestration, retrieval, memory, security, and observability 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