AI Architect
Role Overview
Define and lead architecture for scalable, secure, production-ready enterprise AI/ML and generative AI solutions.
Convert business needs into practical AI architectures across data, models, applications, infrastructure, integration, security, governance, operations, and cost.
Key Skills for This Role
Full Job Posting
Role overview
Define and lead architecture for scalable, secure, production-ready enterprise AI/ML and generative AI solutions.
Convert business needs into practical AI architectures across data, models, applications, infrastructure, integration, security, governance, operations, and cost.
Key responsibilities
- Define end-to-end AI/ML and generative AI architectures and translate business requirements into technical designs.
- Select suitable machine learning, deep learning, LLM, RAG, agentic AI, optimization, or hybrid approaches.
- Design AI platforms for ingestion, processing, model development and serving, APIs, applications, monitoring, and governance.
- Architect LLMs, RAG, vector databases, agents, knowledge bases, orchestration, and cloud-native solutions across Azure, AWS, or GCP.
- Define integration with enterprise applications, APIs, databases, data platforms, and external systems.
- Establish MLOps/LLMOps, lifecycle, monitoring, evaluation, and CI/CD standards; address security, privacy, responsible AI, and compliance.
- Evaluate technologies and platforms, lead proofs of concept and assessments, review designs and risks, and guide engineering teams.
Must-have skills
- 10+ years in software/technology architecture, AI/ML, or related engineering roles.
- Strong understanding of machine learning, deep learning, generative AI, and LLMs; hands-on Python and AI/ML frameworks.
- Strong experience with LLMs, RAG, embeddings, vector databases, agents, and AI orchestration.
- Strong data architecture and pipeline knowledge; experience designing cloud-native, scalable distributed systems.
- Strong knowledge of APIs, microservices, containers, Docker, and Kubernetes.
- Experience with MLOps/LLMOps, model deployment, and monitoring.
- Strong knowledge of security, governance, scalability, performance, availability, and cost optimization.
- Communicate architecture and technical decisions effectively to business, product, engineering, and senior management.
Good to have
- Azure AI, AWS AI, or Google Cloud AI; Azure OpenAI or equivalent enterprise LLM platforms.
- Hugging Face, LangChain, LlamaIndex, MLflow or equivalents; GPU architecture and model optimization.
- Enterprise data platforms, data lakes, lakehouses, Databricks, Microsoft Fabric, computer vision, NLP, forecasting, optimization, AI agents, or enterprise AI governance experience.
Pay
- Pay starts at AED 15,000 per month.
Work location
- Work is in person.
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