Role 1: SAP HCM Architect Role:Job Description:• Hands-on experience with SAP HCM modules (Personnel Administration, Organizational Management, Time Management, Payroll, etc.).• Strong understanding of HR processes and statutory requirements.• Experience with system configuration and troubleshooting in SAP HCM.• Knowledge of SAP ECC; familiarity with migration to SAP S/4HANA is a plus.• Excellent communication, documentation, and interpersonal skills.• Solution Design: Analyze business requirements and design SAP HCM solutions across core modules (PA, OM, Time Management, Payroll, etc.).• Configuration & Customization: Configure SAP HCM modules to meet functional and business requirements.• Support & Maintenance: Provide end-to-end support for HCM-related issues, enhancements, and system updates.• Integration: Work on the integration of SAP HCM with other SAP modules (e.g., FI, SuccessFactors) and third-party systems.• Documentation: Develop functional specifications, technical documentation, and user manuals.• Stakeholder Engagement: Collaborate with HR, Payroll, and IT teams to gather requirements and deliver business-aligned solutions. Role 2: Architect with experience on Oracle ERP implementation Role:Job Description:• Strong functional knowledge of Oracle Cloud ERP• Understanding of technical architecture, data migration, and integration concepts.• Experience with full lifecycle Oracle ERP implementations in a consulting or professional services environment.• Exposure to broader Oracle solutions such as HCM, EPM, or SCM is highly desirable.• Proven ability to lead and manage project teams in complex environments.• Excellent communication, documentation, and presentation skills.• Comfortable working in a client-facing role with the ability to influence senior stakeholders. Role 3: A Cloud Architect specializing in AWS SageMaker:Job Description:Solution Design:o Understanding business requirements and translating them into scalable and efficient machine learning architectures on AWS SageMaker.o Designing end-to-end machine learning pipelines, including data ingestion, processing, model training, deployment, and monitoring.o Selecting appropriate AWS services and features, including SageMaker built-in algorithms, custom models, and other relevant AWS services like S3, EMR, etc.Implementation and Deployment:o Building and deploying machine learning models and infrastructure on AWS SageMaker, including configuring SageMaker instances, endpoints, and pipelines.o Ensuring the scalability, reliability, and security of the machine learning platform.o Implementing best practices for MLOps (Machine Learning Operations) to automate the machine learning lifecycle.Skills and Expertise:• Deep understanding of AWS SageMaker: Including its features, capabilities, and best practices.• Strong knowledge of machine learning concepts: Model building, training, evaluation, and deployment.• Proficiency