AI Solutions Engineer (GenAI / LLM / RAG)

AI Solutions Engineer (GenAI / LLM / RAG)

Location: UAE (Hybrid/Remote)

Employment Type: Full-Time

About the Role

We are looking for an experienced AI Solutions Engineer to join our growing AI team and help design, build, and deploy enterprise-grade Generative AI solutions. You will work on cutting-edge AI applications powered by Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, OCR, semantic search, speech technologies, and modern cloud infrastructure.

This role is ideal for someone passionate about building intelligent AI products that solve real-world business challenges and can take AI solutions from concept to production.

Key Responsibilities

• Design, develop, and deploy enterprise-grade Generative AI applications.
• Build conversational AI assistants with contextual memory and multi-turn conversations.
• Design and implement Retrieval-Augmented Generation (RAG) pipelines.
• Integrate LLMs from leading AI providers into production applications.
• Develop AI agents capable of tool calling, workflow automation, and intelligent reasoning.
• Build semantic search solutions using vector databases and embedding models.
• Develop OCR pipelines for extracting, processing, and indexing documents.
• Integrate Speech-to-Text (STT) and Text-to-Speech (TTS) capabilities.
• Optimize prompts, AI workflows, latency, and operational costs.
• Implement AI guardrails, moderation, and hallucination mitigation techniques.
• Design scalable backend APIs and AI microservices.
• Integrate AI services with web applications, databases, and third-party APIs.
• Monitor AI performance, token usage, response quality, and system reliability.
• Collaborate with product managers, UI/UX designers, and software engineers.
• Produce technical documentation and solution architecture.
• Participate in deployment, testing, optimization, and production support.

Required Technical Skills

• AI & Generative AI
• Strong understanding of Large Language Models (LLMs).
• Experience building production AI applications.
• Hands-on experience with one or more leading AI platforms, such as:
• 1. OpenAI2. Google Gemini3. Anthropic Claude4. Azure AI5. Cohere6. Mistral AI
• Prompt Engineering
• Retrieval-Augmented Generation (RAG).
• AI Agents.
• Semantic Search.
• Embedding Models.
• Context Management.
• AI Evaluation & Optimization.AI Frameworks
• LangChain.
• LangGraph.
• LlamaIndex.
• AI SDKs from major LLM providers.
• MCP (Model Context Protocol) is a plus.

Backend Development

• Python (required).
• FastAPI or Flask.
• REST APIs.
• Async Programming.
• WebSockets.
• Authentication & Authorization.
• Secure API Development.

Databases

• PostgreSQL.
• Redis.
• MongoDB (preferred).
• Supabase (preferred).

Vector Databases

Experience with one or more:

• Qdrant
• Pinecone
• Weaviate
• Milvus
• ChromaDB

OCR & Voice AI

• OCR and Document Intelligence.
• Speech-to-Text (STT).
• Text-to-Speech (TTS).
• Real-time voice interactions.

Cloud & DevOps

Experience with at least one cloud platform:

• Microsoft Azure
• Amazon Web Services (AWS)
• Google Cloud Platform (GCP)

Additional technologies:

• Docker.
• Kubernetes (preferred).
• Git.
• CI/CD Pipelines.

AI Monitoring & Operations

• AI Observability.
• LangSmith or equivalent monitoring platforms.
• Prompt tracing.
• Performance monitoring.
• Token usage tracking.
• Cost optimization.
• AI interaction monitoring.

Nice to Have

• Experience with multilingual AI applications (Arabic & English).
• Knowledge of Responsible AI and AI Governance.
• Experience deploying enterprise-scale AI platforms.
• Experience integrating AI with ERP, CRM, CMS, or enterprise systems.
• Familiarity with AI security, privacy, and compliance best practices.

Qualifications

• Bachelor’s degree in Computer Science, Artificial Intelligence, Software Engineering, Data Science, or a related field.
• 3+ years of sof