Talentus Global

Cloud Engineer

• Design, implement, and manage cloud infrastructure across Azure, AWS, or GCP environments.
• Deploy and maintain scalable, secure, and highly available cloud solutions.
• Automate infrastructure provisioning using Infrastructure as Code (IaC) tools.
• Monitor cloud environments, ensuring performance, reliability, and cost optimization.
• Collaborate with DevOps, development, and security teams to support application deployments.
• Implement and enforce cloud security best practices and compliance standards.
• Manage networking components such as VPCs, subnets, load balancers, and firewalls.
• Troubleshoot cloud infrastructure issues and provide timely resolution.
• Optimize cloud usage and costs through monitoring and right-sizing strategies.
• Stay updated with new cloud services and recommend improvements.

Cloud Engineer – Azure/AWS/GCP

Data Scientist

• Analyze large and complex datasets to identify trends, patterns, and actionable insights that support business decision-making.
• Develop, train, and validate statistical and machine learning models to solve business problems and improve operational performance.
• Apply advanced analytics techniques such as predictive modeling, classification, clustering, and forecasting.
• Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.
• Perform data exploration, cleaning, and feature engineering to prepare datasets for modeling and analysis.
• Design and conduct experiments and A/B tests to evaluate model performance and business impact.
• Communicate insights and model results to technical and non-technical stakeholders through reports, visualizations, and presentations.
• Work with data engineers and ML engineers to deploy models and integrate analytical solutions into production environments.
• Develop dashboards and data visualizations to support business intelligence and reporting needs.
• Ensure data quality, integrity, and proper documentation of analytical processes.

Artificial Intelligence

• Analyze large datasets to identify patterns, trends, and opportunities for applying machine learning solutions.
• Develop, train, and evaluate machine learning models to support business decision-making.
• Collaborate with data engineers and software developers to deploy and maintain AI/ML models in production environments.
• Perform data preprocessing, feature engineering, and model optimization to improve performance and accuracy.
• Design and implement experiments to validate model performance and measure business impact.
• Create dashboards, reports, and visualizations to communicate insights and model results to stakeholders.
• Monitor model performance and retrain models when necessary to maintain reliability and accuracy.
• Support the implementation of responsible AI practices, including model transparency, fairness, and data governance.

AI/ML Analyst

Project Manager

• Lead end-to-end delivery of Microsoft Dynamics 365 projects (CE, F&O, or both), ensuring alignment with scope, timeline, and budget.
• Plan, execute, and monitor project activities using Agile, Scrum, or hybrid methodologies.
• Coordinate cross-functional teams including developers, QA engineers, solution architects, and business stakeholders.
• Manage project scope, risks, issues, and dependencies proactively.
• Facilitate key meetings such as sprint planning, status updates, steering committees, and retrospectives.
• Ensure clear communication between technical teams and business stakeholders.
• Track project progress, KPIs, and deliverables, providing regular reporting to leadership.
• Oversee resource allocation and capacity planning.
• Ensure quality standards and best practices are followed throughout the project lifecycle.
• Support change management, user adoption, and post-go-live activities.

MS Dynamics Project Manager

Solutions Engineer

• Design and architect end-to-end solutions using Microsoft Dynamics 365 (CE, F&O, or both) aligned with business requirements.
• Lead solution design workshops, translating functional needs into scalable technical architectures.
• Define integration strategies between Dynamics 365 and other enterprise systems (Azure, APIs, third-party platforms).
• Collaborate with business stakeholders, product owners, and development teams to ensure successful solution delivery.
• Oversee customization, configuration, and extension of Dynamics 365 environments following best practices.
• Ensure solutions meet performance, security, and compliance standards.
• Provide technical leadership and guidance to developers and consultants throughout the project lifecycle.
• Review and validate solution design, code, and architecture to ensure quality and maintainability.
• Support deployment strategies, DevOps processes, and environment management.
• Stay updated with Microsoft ecosystem innovations and recommend improvements or optimizations.

MS Dynamics Solution Architect

Consultant

• Gather, analyze, and document business requirements.
• Configure and customize Microsoft Dynamics 365 modules (e.g., Finance, Supply Chain, Sales, Customer Service).
• Translate business needs into functional specifications for technical teams.
• Collaborate with developers, QA teams, and stakeholders to deliver solutions.
• Support system integrations, data migration, and testing activities.
• Conduct UAT sessions and provide end-user training.
• Troubleshoot functional issues and provide ongoing system support.
• Ensure best practices and standardization across implementations.

MS Dynamics Functional Consultant

QA Engineer

• Design, develop, and execute test plans and test cases for Microsoft Dynamics 365 solutions (CE, F&O, or both).
• Perform functional, integration, regression, and user acceptance testing (UAT) support.
• Validate customizations, configurations, and integrations within Dynamics 365 environments.
• Collaborate with developers, solution architects, and business analysts to understand requirements and ensure quality delivery.
• Identify, document, and track defects using test management and tracking tools.
• Ensure data integrity and system performance through thorough testing processes.
• Participate in Agile ceremonies (sprint planning, daily stand-ups, retrospectives).
• Automate test scenarios where applicable using appropriate tools and frameworks.
• Support release validation and post-deployment testing activities.
• Continuously improve QA processes, standards, and best practices.