Role: Full Stack Data Scientist (Azure AI Engineer)
Location: Dubai, UAE
Notice: 30 days max
Experience: 5+ years
Duration: 6+ months extendable
Payroll: Dautom Information Technology
Job Summary
We are looking for a highly capable Full Stack Data Scientist / Azure AI Engineer who can build end-to-end AI products: data + ML/DL/CV models + Agentic workflows + APIs + UI + scalable deployment on Kubernetes (AKS). The role requires deep expertise in the Azure AI ecosystem (Azure Machine Learning, Azure AI Foundry, Azure AI Search) and strong hands on experience building AI agents using LangChain, LangGraph, and/or Microsoft Agent Framework, with Langfuse for tracing, evaluation, and observability.
The ideal candidate has shipped production systems with measurable business impact and can operate them reliably through strong MLOps/LLMOps practices.
Proven Experience (Non-Negotiable)
- Demonstrated end-to-end delivery of AI applications in production (build deploy operate), with measurable impact.
Key Focus Areas
AI Agents & GenAI Systems
- Build intelligent agent workflows using LangChain, LangGraph, and Microsoft Agent Framework
- Design multi-step, tool-using, autonomous AI systems with memory, routing, and collaboration logic
- Implement safety, governance, and prompt-injection protection mechanisms
Azure AI Ecosystem (Must-Have)
- Azure Machine Learning (training, deployment, MLOps pipelines)
- Azure AI Foundry (prompt orchestration, GenAI workflows)
- Azure AI Search (RAG pipelines, vector & hybrid search, semantic ranking)
MLOps / LLMOps
- Implement Langfuse for tracing, evaluation, monitoring, and cost tracking
- Build evaluation frameworks for RAG and agent systems
- Ensure continuous improvement and production reliability
ML / DL / Computer Vision
- Develop models for classification, detection, segmentation, OCR, and anomaly detection
- Optimize performance, accuracy, and scalability in production environments
Engineering Stack
- Python (FastAPI), Node.js APIs
- React (AI dashboards, chat interfaces, agent UI)
- Docker + Kubernetes (AKS deployment)
Cloud & DevOps
- CI/CD pipelines for ML + application deployment
- Monitoring via Azure Monitor / Application Insights
- Secure, scalable, production-ready architecture
Core Technical Skills
- Agents/Frameworks: Strong hands-on experience with LangChain, LangGraph, and Microsoft Agent Framework.
- LLMOps: Strong experience with Langfuse for tracing/evaluation/monitoring (or equivalent tooling, with Langfuse preferred).
- Azure: Azure ML, Azure AI Foundry, Azure AI Search; plus Key Vault, Storage, App Insights/Monitor as needed.
- Programming: Strong Python; API development with FastAPI; Node.js for services/integrations.
- Frontend: React for production UI development.
- ML/DL/CV: Proven hands-on depth in ML/DL and Computer Vision.
- Deployment: Docker + Kubernetes/AKS.
- Data: Strong SQL; experience with structured + unstructured data.
Preferred Qualifications
- Experience in real estate / construction domain AI use cases (valuation, forecasting, risk, customer support automation).
- Exposure to graph databases (e.g., Neo4j) and vector search/vector databases for AI applications.
- Extra certifications (nice-to-have): Azure Fundamentals (AZ-900), Azure Developer (AZ-204), Kubernetes (CKA/CKAD), Databricks ML.
Interested candidates can share their CVs at [HIDDEN TEXT] or connect with Shaloo Rani on LinkedIn here
