Assistant Manager - AI/ML Engineer

• Design, build, and deploy scalable and reliable AI/ML models using Azure services such as Azure AI Foundry, Azure Machine Learning, and Azure Cognitive Services.
• Implement and fine-tune deep learning models, including traditional Neural Networks (NNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Large Language Models (LLMs), for a variety of use cases across NLP and computer vision domains.
• Apply knowledge of Agentic AI frameworks to design systems capable of autonomous decision-making and task execution.
• Integrate LLMs and other AI models with external data sources and tools using standardized frameworks like the Model Context Protocol (MCP) to enhance model capabilities.
• Develop and maintain data pipelines for ingestion, preprocessing, and transformation using Azure Data Factory and Azure Databricks.
• Manage the full lifecycle of machine learning models, including deployment, monitoring, and maintenance, applying MLOps best practices.
• Ensure the security, performance, and scalability of AI solutions through robust monitoring and optimization strategies.
• Collaborate with development teams to integrate AI models into new and existing applications built with technologies like .NET and Python.
• Develop server-side logic using Node.js and integrate AI models with web applications using Application-to-Application (A2A) patterns and Azure Integration Services.
• Work with stakeholders to define requirements and translate business needs into technical solutions.
  

Required Skills And Qualifications

• Bachelor’s or master’s degree in computer science, Artificial Intelligence, or a related field.Minimum of five years of proven experience as an AI/ML Engineer, with a strong focus on designing and deploying solutions on the Azure cloud platform during the last few years.
• Strong programming proficiency in Python for machine learning and data analysis.
• Proficiency in Node.js for back-end development.
• Hands-on experience with Azure AI/ML services, including Azure Machine Learning, Azure OpenAI, and Azure Cognitive Services.
• Knowledge of prompt engineering and Retrieval-Augmented Generation (RAG) techniques.
• Understanding of machine learning algorithms and deep learning frameworks, with experience in neural network architectures (NNs, CNNs, RNNs) and LLMs.
• Familiarity with NLP and computer vision techniques and applications.
• Exposure to Agentic AI frameworks and their application in real-world systems.
• Solid understanding of both SQL and NoSQL databases, including Azure SQL and Cosmos DB.
  

Desirable Skills And Qualifications

• Familiarity with Microsoft Power Apps and the .NET framework.
• Experience with Azure services such as Azure Web Apps, Azure Functions, Azure Container Instances, and Azure Integration Services.
• Experience with Azure Data Factory, Azure Databricks, and Azure Blob Storage.
• Experience with Model Context Protocol (MCP) for connecting AI systems to external data and tools.
• Understanding of Application-to-Application (A2A) integration patterns and architectures.
• Knowledge of MLOps tools and CI/CD pipelines for automating the ML lifecycle.
• Experience with Docker and Kubernetes for containerization and orchestration.