Lead the development and deployment of Generative AI models using Azure OpenAI, LLMs, and Agentic AI frameworks.
Architect and implement end-to-end AI solutions on Azure Machine Learning, Azure OpenAI, and SageMaker (as needed).
Design and optimize Natural Language Processing (NLP) pipelines for enterprise-grade applications.
Apply Retrieval-Augmented Generation (RAG) and neural network architectures to enhance model performance.
Collaborate with cross-functional teams to understand business needs and translate them into AI-driven solutions.
Ensure best practices in model governance, security, and compliance within the Azure ecosystem.
Guide and mentor junior engineers and data scientists in GenAI development and deployment.
Stay current with advancements in Generative AI, LLMs, and cloud-native ML platforms.
Your Profile
10+ years of experience in Machine Learning, Deep Learning, and AI, with at least 3+ years in Generative AI.
Proven experience with Azure OpenAI, Azure Machine Learning, and LLM-based solutions.
Strong understanding of Agentic AI, RAG, and neural networks.
Proficiency in Python and AI/ML frameworks such as TensorFlow, PyTorch, etc.
Experience with cloud platforms including Azure, AWS SageMaker, and Google Vertex AI.
Ability to design, implement, and scale AI models for production environments.
Strong analytical and communication skills to interpret complex data and present insights to stakeholders.
Familiarity with AI platform capabilities and limitations, ensuring optimal solution design.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Data Science & Machine Learning - OtherEmployement Type: Full time