AI Engineer - Azure

Notice

Experience

Duration

Job Summary

Proven Experience (Non-Negotiable)

• Demonstrated end-to-end delivery of AI applications in production (build → deploy → operate), with measurable impact.

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

• 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 shaloo.rani@dautom.com or connect with

Shaloo Rani