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Responsibilities Full Stack GCP Cloud Engineer
· Develop and design AI solutions which include components across Chatbots, Virtual Assistants, and Machine Learning
· Collaborate with peers across multiple technology disciplines ensuring AI platform and solutions deliver business and technical requirements
· Lead technical workshops in driving strategic initiatives, while developing and managing relationships both internal and external vendors
· Serve program teams to better understand their problems and goals, recommending possible solutions and building consensus around architecture
· Oversee and manage the full AI program life cycle implementations
· Assist, guide, and drive engineering teams by providing technical oversight during implementation and owning technical delivery
· · Ensure all architectural consideration and non-functional requirements around high availability, scalability, maintainability, and extensibilities are factored in in the core system.
· Implement POC, sample use case, and core platform components for a highly scalable application
Google Vertex AI, Google Big Query, Google DataPlex, Google Data Catalog, Cloud Functions, Cloud Composer, Kubernetes on Google, Networking and Firewall knowledge good to have
· Experience implementing, developing and deploying enterprise AI solutions involving Advanced Analytics, Machine Learning and Data Science specifically on Google Cloud ENvironment
· Experience with AI architecture and AI interface design covering diverse range of use cases and deployment models
· In-depth knowledge of components and architectural trade-offs across data management, governance, model building and production workflows of AI on GCP is a must
· Understand the workflow and planning pipeline architectures of ML and deep learning frameworks, with data, training/retraining and deployment
· Demonstrated expertise in modeling techniques with types of algorithm and development at least one of the following machine learning, deep learning, time-series, anomaly detection and prediction
· In-depth theoretical and practical knowledge in few select areas across AI cloud spectrum GCP AI/ML Services and MS Azure ML Services. Google cloud Certification is preferrable
· Knowledge and ability to apply OOPS concepts, SOLID principles, and design patterns.
· Experience with Computer Science fundamentals in data structures, algorithms, and complexity analysis
· Good Analytical skills.
Additional InformationThese jobs might be a good fit

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Role Overview:
The platform will involve IoT, real-time data processing, and event-driven architectures to support device onboarding, monitoring, and control.
Key Responsibilities:
Required Skills:
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The SAP Commissions Specialist will be responsible for the implementation and ongoing maintenance of SAP Commissions solutions and the SAP Commissions Platform. This role involves close collaboration with functional teams and partners to thoroughly understand their challenges, ensuring rapid and effective resolution of issues (break fixes). Additionally, the Specialist will deliver technical solutions for Service Requests and Enhancements based on business requirements.
Conduct research, analysis, and troubleshooting to diagnose and resolve technical issues
Collaborate with stakeholders, functional counterparts to gather and analyze business requirements and translate them into functional specifications.
Document Functional Requirements and Solution Designs.
Serve as the primary technical contact for functional counterparts and partners.
Involving in Designing, configuration, testing, and deployment of complex commission rules and structures within the SAP Commissions platform
- Over 6 years of experience as a skilled SIP Technical Architect, particularly in SAP Commissions.
- In-depth understanding of all SAP Commission components.
- Familiarity with compensation plans and bonuses, including the implementation of compensation rules in SAP Commissions using various components.
- Strong ability to learn and adapt to new technology products and programming languages.
- Strategic problem-solving skills and the ability to think critically.
- Excellent organizational skills, capable of managing multiple tasks simultaneously.
- Strong interpersonal skills, with experience engaging with audiences across all technical and management levels.
- Demonstrated eagerness to contribute to a collaborative team environment with a positive, "can-do" attitude.
- Exceptional written and verbal communication skills.- Bachelor’s or Master’s degree in a technology-related field or equivalent qualifications.
- Minimum of 6 years of experience in Application Maintenance, specifically with Callidus/SAP Commissions products.
- At least 3 years of experience with CDL/XDL, Advanced Workflow, and Embedded Analytics.
- Ability to design, develop, and maintain SAP Commission rules and configurations.
- Experience managing users through IAS, IPS, and ThunderBridge.
- Proficient in designing, developing, and maintaining workflows for SAP Commissions.
- Familiarity with building stories in Embedded Analytics.
- Proficient knowledge of the Commissions HANA DB data model.
- Expertise in SAP T&Q is a plus.
- Strong domain expertise, technical aptitude, and the capability to quickly acquire new technical skills.
- Experience in enterprise-level SPM implementation..
These jobs might be a good fit

Responsibilities Full Stack GCP Cloud Engineer
· Develop and design AI solutions which include components across Chatbots, Virtual Assistants, and Machine Learning
· Collaborate with peers across multiple technology disciplines ensuring AI platform and solutions deliver business and technical requirements
· Lead technical workshops in driving strategic initiatives, while developing and managing relationships both internal and external vendors
· Serve program teams to better understand their problems and goals, recommending possible solutions and building consensus around architecture
· Oversee and manage the full AI program life cycle implementations
· Assist, guide, and drive engineering teams by providing technical oversight during implementation and owning technical delivery
· · Ensure all architectural consideration and non-functional requirements around high availability, scalability, maintainability, and extensibilities are factored in in the core system.
· Implement POC, sample use case, and core platform components for a highly scalable application
Google Vertex AI, Google Big Query, Google DataPlex, Google Data Catalog, Cloud Functions, Cloud Composer, Kubernetes on Google, Networking and Firewall knowledge good to have
· Experience implementing, developing and deploying enterprise AI solutions involving Advanced Analytics, Machine Learning and Data Science specifically on Google Cloud ENvironment
· Experience with AI architecture and AI interface design covering diverse range of use cases and deployment models
· In-depth knowledge of components and architectural trade-offs across data management, governance, model building and production workflows of AI on GCP is a must
· Understand the workflow and planning pipeline architectures of ML and deep learning frameworks, with data, training/retraining and deployment
· Demonstrated expertise in modeling techniques with types of algorithm and development at least one of the following machine learning, deep learning, time-series, anomaly detection and prediction
· In-depth theoretical and practical knowledge in few select areas across AI cloud spectrum GCP AI/ML Services and MS Azure ML Services. Google cloud Certification is preferrable
· Knowledge and ability to apply OOPS concepts, SOLID principles, and design patterns.
· Experience with Computer Science fundamentals in data structures, algorithms, and complexity analysis
· Good Analytical skills.
Additional InformationThese jobs might be a good fit