Key Responsibilities:
•    Design cloud-native AI architectures for personalized recommendations, conversational systems, and real-time analytics.
•    Leverage generative AI technologies like LangChain and RAG to build advanced AI solutions.
•    Train, fine-tune, and deploy ML models using Microsoft Copilot Studio, Power platform, Azure ML, AWS SageMaker, AWS bedrock
•    Implement CI/CD pipelines for seamless model updates and scaling.
•    Build and optimize ETL workflows for large-scale data processing using Azure Data Factory and AWS Glue.
•    Integrate data pipelines with AI/ML models to enable real-time decision-making.
•    Deploy robust MLOps practices, including automated monitoring and model retraining.
•    Enhance AI model security through advanced techniques like LLM Guard and PromptInject.
•    Collaborate with stakeholders to define AI use cases and ensure alignment with business objectives.
•    Document AI workflows, data pipelines, and deployment processes for reproducibility. Requirements:
•    5+ Years of experience in code development wih Java, Python, Vscode
•    Proficiency in PyTorch, TensorFlow, and deep learning frameworks.
•    Experience with Azure Cognitive Services, AWS AI/ML tools, and cloud-native architectures.
•    Strong understanding of containerization, orchestration, and serverless computing.
•    Hands-on experience with cloud automation tools like Terraform and Kubernetes.
•    Proven ability to troubleshoot complex AI/ML workflows and deliver scalable solutions.
•    Strong leadership and project management skills to handle multi-disciplinary projects.
•    Solid understanding of NLP, computer vision, reinforcement learning, and time series forecasting.