REQUIRED SKILLS:

• Experience with Power Apps, Power automate, Plugins, AI Builder, CoPilot and related architecture and design practices
• Experience with Azure, Azure DevOps for CI/CD and C#.net.
• Proven experience in developing and deploying AI models and algorithms.
• Proficiency in programming languages such as Python, Java, or C#.
• Strong knowledge of AI frameworks and libraries such as TensorFlow, PyTorch, or similar.
• Experience in the following technologies - Microsoft Dynamic 365 Customer Engagement
• Experience of iterative / agile development practices
• Strong problem solving and troubleshooting skills with the ability to exercise mature judgment.
• Excellent communication skills

DESIRED SKILLS:

• Dynamics / Power Platform / Azure certifications
• Familiar with basic Machine Learning concepts
• Knowledge of Enterprise Architecture Patterns
• Experience with full lifecycle application testing (functional, regression, performance, integration, etc.) and delivery management.
• Comfortable with direct interaction with the business users at all levels

SPECIFICALLY, THE PERSON WILL BE RESPONSIBLE FOR THE FOLLOWING -

• Design, develop, and implement AI models and algorithms using Microsoft technologies.
• Collaborate with data scientists and business stakeholders to understand requirements and design effective AI solutions.
• Build and maintain scalable, high-performance AI infrastructure on the Microsoft Azure platform, AI Builder and Co-pilot with Dynamics
• Develop and deploy machine learning models using Machine Learning, Cognitive Services, Bot Framework, and other Azure AI tools.
• Optimize AI algorithms for performance and scalability.
• Conduct thorough testing and validation of AI models to ensure accuracy and reliability.
• Document and communicate AI solutions and recommendations to technical and non-technical stakeholders clearly and effectively.
• Evaluates AI technologies (such as LLMs, SLMs, embeddings) and architectures (such as orchestration patterns, RAG, etc) when developing solutions. Specifies or implements AI platform improvements like fine-tuning or training custom ML models.