AGENTIC

• Lead and execute SAP cloud projects, participating in the design, implementation, and deployment of SAP solutions on public cloud platforms.
• Advise clients by providing technical and strategic expertise on SAP best practices and cloud optimization.
• Monitor and optimize SAP system performance in the cloud to ensure scalability, efficiency, and cost optimization.
• Diagnose and resolve SAP and cloud-related technical incidents.
• Create and maintain detailed technical documentation for architectures, configurations, and implementations.
• Collaborate with cross-functional internal teams (development, operations, etc.) to ensure successful delivery.
• Stay current on the latest SAP and public cloud technologies, trends, and best practices.

SAP Consultant, Public Cloud

Business Analyst

• Create detailed requirements and lead the execution of integration projects.
• Document and manage business logic in automations using UiPath.
• Administer workflows and intelligent data capture in GlobalCapture.
• Ensure alignment between business stakeholders and the development team.

Data Engineer

• Design, develop, and maintain data engineering pipelines using Azure Synapse Analytics and Databricks to support data warehousing and advanced analytics.
• Develop interactive and informative dashboards and reports using Power BI for business decision-making.
• Implement data integration, data modeling, and ETL/ELT processes, ensuring data quality and consistency across platforms.
• Migrate and integrate data from SAP systems (SAP ECC, BPC, APO, SAP BI) to cloud-based environments and analytical tools.
• Collaborate with cross-functional teams to understand data requirements and provide data-driven solutions for business needs.
• Apply machine learning frameworks and tools for predictive analytics and data science projects.
• Ensure data governance, security, and compliance best practices are followed throughout all data processes.
• Manage and optimize data lake and data warehousing solutions to support efficient data processing and storage.

SAP-Azure Data Engineer

Android Engineer

• Design, build, and maintain high-performance, scalable Android applications using Kotlin (primary) and Java (when needed).
• Collaborate closely with product managers, designers, QA engineers, and backend teams to define requirements and deliver polished features.
• Translate business and user requirements into clean, maintainable, and testable code following modern Android architecture best practices (MVVM, MVI, Clean Architecture).
• Implement pixel-perfect UI/UX following Material Design 3 guidelines and ensuring excellent performance across a wide range of Android devices and OS versions.
• Integrate REST/GraphQL APIs, handle offline support, data persistence (Room,DataStore), secure authentication, push notifications, and analytics.
• Write robust unit, integration, and UI tests (JUnit, Espresso, Robolectric, MockK).
• Participate in code reviews, architectural discussions, and continuous improvement of the mobile codebase.
• Localize app content and UI strings for English and Spanish-speaking users; adapt features to regional preferences and compliance requirements.
• Communicate effectively in both English and Spanish during meetings, documentation, user support tickets, and stakeholder updates.
• Debug and resolve production issues quickly while maintaining high code quality and app stability.
• Stay current with Android ecosystem changes (new Jetpack libraries, Kotlin Multiplatform Mobile when relevant, Google Play policies, etc.)

Android Developer

Artificial Intelligence

• Design and implement context pipelines for LLM-based systems.
• Structure information to maximize model understanding and response quality.
• Define strategies for prompt composition, context injection, and tool usage.
• Build and optimize RAG pipelines using vector databases.
• Implement document ingestion, chunking, embedding, and retrieval strategies.
• Improve retrieval precision and reduce hallucinations in AI outputs.
• Design and maintain prompt frameworks for AI agents and applications.
• Optimize prompts through systematic testing and evaluation.
• Integrate prompts with tool use, APIs, and agent workflows.
• Structure knowledge bases for AI consumption.
• Implement pipelines for data preprocessing, indexing, and embedding generation.
• Manage semantic search and knowledge retrieval systems.
• Analyze model performance and improve context efficiency.
• Monitor latency, token usage, and system scalability.
• Develop evaluation methods to measure prompt and context performance.
• Work closely with AI Engineers, Data Engineers, and Product Teams.
• Translate business requirements into AI-powered solutions.
• Document context architectures and AI workflows.

SAP Consultant, Public Cloud

Business Analyst

SAP-Azure Data Engineer

Android Developer

AI Context Engineer