Azure Solutions AI&ML Workloads Architect

Overview

Lead the design and delivery of AI/ML-driven solutions on Azure. Partner with data scientists, engineering teams, and business stakeholders to create enterprise-grade architectures that enable advanced analytics, machine learning, and cognitive services at scale.

Job Description

Key Responsibilities

Design and implement scalable, secure, and cost-optimized AI/ML architectures on Microsoft Azure.

Architect AI/ML workloads leveraging Azure Machine Learning, Azure OpenAI, Cognitive Services, Synapse, and Databricks.

Define and oversee data engineering and MLOps pipelines, including ingestion, training, deployment, and monitoring of models.

Integrate ML frameworks (TensorFlow, PyTorch, Scikit-Learn) with Azure services for enterprise-grade solutions.

Lead cloud strategy, governance, security, and compliance initiatives for AI/ML workloads.

Collaborate with data scientists, engineers, and business stakeholders to align technical solutions with business goals.

Deliver technical presentations and proposals, translating designs into clear business value.

Stay updated on emerging Azure AI/ML services and recommend adoption of innovative capabilities.

 

Key Requirements

Deep expertise in Microsoft Azure: design and implementation of scalable, secure, and cost-optimized architectures.

Proven experience architecting AI/ML workloads using Azure Machine Learning, Azure OpenAI, Cognitive Services, Synapse, and Databricks.

Strong understanding of data engineering and MLOps pipelines—data ingestion, model training, deployment, and monitoring.

Familiarity with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn) and their integration with Azure services.

Ability to lead end-to-end cloud strategy, governance, security, and compliance for AI/ML solutions.

Excellent communication skills to translate technical designs into business value.

 

Preferred certifications: Microsoft Certified: Azure Solutions Architect Expert and Azure AI Engineer Associate

Skills & Requirements

Microsoft Azure, Azure Machine Learning, Azure OpenAI, Cognitive Services, Synapse, Databricks, Data engineering, MLOps pipelines, Model training, Model deployment, Model monitoring, TensorFlow, PyTorch, Scikit-Learn, Cloud security, Cloud governance, Compliance, Solution architecture, Communication skills, Microsoft Certified Azure Solutions Architect Expert (preferred), Azure AI Engineer Associate (preferred).

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