•Build evaluation frameworks and guardrails
•Build secure scalable backend APIs for AI workloads
•Create observability reliability and performance metrics
•Decompose ambiguous problems into deliverable plans
•Deploy and operate AI applications on cloud
•Design and build agentic AI systems with LLMs
•Identify AI use cases and scope solutions
•Implement CI/CD pipelines
•Implement authentication logging and monitoring
•Maintain and improve production ML and DL models
•Orchestrate multi-agent workflows
•Retrain evaluate and tune models
•Route field learnings into platform tooling and roadmap
•Turn bespoke builds into reusable internal components
Технологии: .NET, API Design, Agent Orchestration, App Service, Azure App, Azure App Service, Azure DevOps, Azure Functions, Azure OpenAI, Azure Storage, C#, CI/CD, Deep learning, Docker, Drift monitoring, Function Calling, Guardrails, LLM Evaluation, Language Models, Large Language Models, MCP, Machine Learning, Microsoft Azure, Model Drift, Model drift monitoring, NodeJs, Observability, Prompt engineering, Python, REST API, REST API design, Retrieval-Augmented Generation, Tool/function calling, Vector Databases