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Designs and maintains scalable data pipelines and ETL/ELT workflows using Python, SQL, and Azure Databricks. Manages large structured and semi-structured datasets, data models, monitoring, quality controls, troubleshooting, and production support. Integrates LLM and Generative AI capabilities, including APIs, embeddings, prompt engineering, and RAG workflows, into data solutions. Collaborates with engineering, analytics, and business teams while following security, CI/CD, documentation, and maintainability best practices.

Manage Agile project delivery across product managers, program managers, and cross-functional teams. Maintain schedules, backlogs, dashboards, and project metrics; facilitate Agile ceremonies; manage risks and dependencies; oversee multiple initiatives; provide portfolio visibility and leadership updates; and drive continuous process improvement and transparent stakeholder communication.

Develop and maintain full-stack .NET applications using C#, C/C++, AngularJS, and WinForms. Responsibilities include implementing features, debugging defects, conducting manual and automated testing, maintaining Azure DevOps pipelines and test infrastructure, performing code reviews, resolving incidents, and addressing security and compliance issues. The role collaborates with cross-functional teams and may require occasional onsite travel for training or project stabilization.

Build and deploy production-ready AI agents and multi-agent systems on Azure. Design RAG pipelines, orchestration patterns, tool integrations, APIs, prompt engineering workflows, evaluation loops, and unstructured-data pipelines. Implement CI/CD, monitoring, responsible AI controls, and enterprise integrations with Microsoft Teams and M365 Copilot. The role requires hands-on GenAI/LLM engineering, Python development, cloud infrastructure expertise, and flexibility across data engineering, low-code configuration, and AI-native development tools.