• API Development: Design, build, and maintain RESTful APIs using .NET C#, focusing on performance, reliability, and security. • Entity Framework & SQL: Develop efficient data models using Entity Framework Core, and write optimized SQL queries for relational databases like SQL Server. • Cloud Transition Support: Contribute to new development efforts that utilize Azure services (e.g., Azure Functions, App Services, Azure SQL) as we begin migrating from on-prem infrastructure. • Machine Learning Integration: Collaborate with stakeholders to integrate machine learning models via RESTful APIs or Azure ML services. • Clean, Maintainable Code: Follow best practices to write testable, maintainable, and well-documented code. • Cross-Team Collaboration: Work closely with fellow developers and business partners to deliver secure, scalable solutions. • CI/CD Practices: Support continuous integration and delivery efforts using tools like GitHub Actions. • Problem Solving: Investigate and resolve performance issues, bugs, and bottlenecks in existing systems.

• The work involves designing and implementing AI solutions aligned with business needs and technological standards. • It includes applying techniques like Retrieval-Augmented Generation (RAG) to improve the precision and relevance of AI interactions. • Developing Agentic RAGs, which incorporate autonomous agents to refine data retrieval and content generation. • Developing AI agents and agent networks, capable of solving complex problems and interacting with each other. • Using tools such as LangChain to create modular architectures for agents. • Designing and managing data ingestion pipelines, implementing serverless architectures and Pub/Sub models to scale data intake. • Using DevOps and MLOps practices for automating the deployment and management of AI models. • Integrating APIs to connect AI models with external systems and to register events and metadata. • Performance optimization includes analyzing system performance, detecting bottlenecks, and implementing caching strategies to improve response times. • Emphasizing collaboration with designers and product teams to ensure AI solutions meet real business and user needs, while maintaining innovation through continuous research and experimentation with new AI technologies.

• Operate within project-specific frameworks while collaborating with cross-functional team members, including product managers, UX designers, and front-end developers • Recommend and implement innovative solutions to drive continuous improvement • Develop and implement new features, as well as enhance and optimize existing functionalities • Partner with product owners to translate strategic objectives into actionable backlog items • Engage with end users to address feature requests and resolve reported issues • Formulate and enforce rigorous testing methodologies

• Design and develop infrastructure APIs in Go for cloud resource management. • Implement REST and gRPC endpoints across the cloud platform API surface. • Contribute to backend service architecture: API design, data models, service communication. • Integrate services with the platform ecosystem: IAM, Terraform provider, OpenStack, Kubernetes. • Maintain and improve CI/CD pipelines and release automation. • Own services end-to-end: from development through production monitoring and incident response.