AI/ML Engineer – Azure & GenAI

We are seeking a skilled AI/ML Engineer specializing in Microsoft Azure and Generative AI (GenAI). This role involves designing, developing, and deploying AI solutions using LLMs, RAG systems, and MLOps best practices within the Microsoft ecosystem. Ideal candidates will have experience with LangChain, LangGraph, Azure Machine Learning, and vector databases, contributing to scalable, secure AI systems.

Key Responsibilities include:

• Developing and deploying AI/ML models using Python, Azure Machine Learning, and Generative AI frameworks.
• Building LLM-powered applications using tools like LangChain, LangGraph, FAISS, and Pinecone.
• Implementing and maintaining RAG (Retrieval-Augmented Generation) workflows in production environments.
• Integrating AI solutions with Azure services like Functions, Data Lake, Synapse, and Cognitive Services.
• Applying MLOps principles using Azure DevOps, Docker, and CI/CD pipelines for model lifecycle management.
• Monitoring and optimizing model performance for accuracy, scalability, and reliability.
• Collaborating with cross-functional teams, including data scientists, engineers, and business stakeholders.
• Ensuring adherence to security, compliance, and governance in AI solution deployments.
• Staying updated on Azure AI, Generative AI, and machine learning trends.

Required Qualifications & Skills:

• Bachelor's or Master’s degree in Computer Science, AI/ML, Data Science, or related field.
• 5+ years of hands-on experience in AI/ML model development using Python.
• Experience with Large Language Models (LLMs) like GPT, Gemini, or similar.
• 1+ years of experience with Generative AI and RAG-based systems in production.
• Proficiency with LangChain, LangGraph, and vector DBs (FAISS, Pinecone).
• Solid understanding of deep learning and NLP architectures (Transformers, CNNs, RNNs).
• Practical knowledge of PyTorch, TensorFlow, Keras, Scikit-learn, Pandas, and NumPy.
• Experience with Azure AI stack (Azure ML, Azure Functions, Azure DevOps).
• Familiarity with Docker, REST APIs, and CI/CD pipelines.
• Excellent problem-solving, analytical, and communication skills.

Preferred / Nice-to-Have:

• Azure Certifications – Azure AI Engineer Associate or Azure Data Scientist Associate.
• Experience with MLOps frameworks and model lifecycle management.
• Knowledge of healthcare data standards (e.g., X12, HL7).
• Familiarity with Power BI or other Microsoft analytics tools.