As an AI Engineer, you will be responsible for designing, developing, and implementing AI models and algorithms that enhance the company’s products and services. You will collaborate with cross-functional teams to integrate AI solutions into various applications, ensuring they are scalable, efficient, and effective. Your role will involve working with large datasets, developing machine learning models, and deploying them into production environments.

 Responsibilities

• Model Development: Design, develop, and implement machine learning models and algorithms to address specific business challenges.
• Data Handling: Collect, preprocess, and analyze large datasets to extract meaningful insights and prepare them for model training.
• AI Solution Integration: Work closely with software engineers, data scientists, and product managers to integrate AI models into production systems.
• Research & Development: Stay up-to-date with the latest advancements in AI and machine learning, and apply these techniques to improve existing models or develop new ones.
• Performance Optimization: Continuously monitor and optimize the performance of AI models, ensuring they meet the required accuracy, efficiency, and scalability standards.
• Documentation: Create detailed documentation for AI models, algorithms, and processes to ensure transparency and reproducibility.
• • Collaboration: Work with cross-functional teams, including data engineers, software developers, and business stakeholders, to deliver AI-driven solutions.

 Qualifications

As a Cloud Architect, you will be responsible for designing and implementing cloud-based solutions that meet the business and technical requirements of our organization. You will play a critical role in planning and executing our cloud strategy, ensuring that our systems are scalable, secure, and highly available.

 Responsibilities

• Cloud Migration Leadership: Lead end-to-end cloud migration projects from on-premises environments to AWS and Azure platforms. Develop migration strategies, assess existing infrastructure, and execute migration plans with minimal disruption to business operations.
• Architecture Design: Design robust, scalable, and secure cloud architectures on AWS and Azure to meet the requirements of enterprise-level applications and services. Ensure architectures align with industry best practices and compliance standards.
• Technical Leadership: Provide technical leadership and guidance to cross-functional teams throughout the project lifecycle. Mentor junior team members and facilitate knowledge sharing sessions to promote continuous learning and skill development.
• Infrastructure Automation: Implement infrastructure as code (IaC) principles using tools such as Terraform, CloudFormation, or ARM templates to automate provisioning, configuration, and management of cloud resources.
• Performance Optimization: Optimize cloud infrastructure for performance, scalability, and cost-efficiency. Monitor system performance metrics, identify areas for improvement, and implement optimization strategies to enhance overall system performance.
• Security and Compliance: Implement robust security measures and compliance controls to protect cloud environments from security threats and ensure adherence to regulatory requirements. Conduct security assessments, implement security best practices, and develop incident response plans.
• Cloud Governance: Establish and enforce cloud governance policies, standards, and procedures to maintain operational efficiency and compliance across multiple cloud environments. Implement cost management strategies to optimize cloud spending and resource utilization.
• Collaboration and Communication: Collaborate with stakeholders, including business leaders, development teams, and operations teams, to understand business requirements and translate them into technical solutions. Communicate project status, risks, and issues effectively to stakeholders and senior management.

• Bachelor’s degree in Computer Science, Information Technology, or related field. Master’s degree preferred.
• 10+ years of experience in IT infrastructure, with at least 5 years of experience in cloud architecture and migration.
• In-depth knowledge of AWS and Azure cloud platforms, including services such as EC2, S3, RDS, Lambda, Virtual Machines, Azure Blob Storage, Azure SQL Database, etc.
• Strong understanding of cloud migration methodologies, tools, and best practices.
• Proficiency in scripting and programming languages such as Python, PowerShell, or Bash.
• Experience with containerization technologies (Docker, Kubernetes) and serverless computing.
• Solid understanding of networking concepts, security principles, and compliance requirements.
• Excellent problem-solving skills and the ability to work effectively in a fast-paced environment.

• AWS Certified Solutions Architect (Professional) or equivalent.
• Microsoft Certified: Azure Solutions Architect Expert or equivalent.
• Additional certifications such as AWS Certified DevOps Engineer, AWS Certified Security – Specialty, or Azure Security Engineer Associate are a plus.

As a Senior Data Engineer, you will be responsible for designing, developing, and maintaining scalable data solutions on Microsoft Azure. You will work closely with data scientists, analysts, and other stakeholders to ensure data is readily available, clean, and accurate for business intelligence, analytics, and machine learning purposes. Your role will involve leveraging Azure services to build and optimize data pipelines, manage data warehouses, and ensure data security and compliance.

Responsibilities

• Design, develop, and maintain scalable and efficient data pipelines using Azure and Synapse Pipeline Development.
• Collaborate with cross-functional teams to understand data requirements and translate them into robust data engineering solutions.
• Develop and optimize ETL (Extract, Transform, Load) processes to ensure reliable and timely data delivery.
• Implement data quality checks, data validation, and data cleansing techniques to ensure data accuracy and consistency.
• Utilize Azure services such as Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake Storage to build and manage data pipelines.
• Integrate and migrate existing data workflows to Azure-based solutions.
• Monitor and troubleshoot data pipeline performance, ensuring high availability and reliability.
• Optimize data storage and retrieval mechanisms to support efficient data access and analysis.
• Collaborate with data scientists and analysts to provide clean, consistent, and reliable data for advanced analytics and machine learning projects.
• Stay up-to-date with the latest trends, technologies, and best practices in the data engineering domain. 

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related field.
• 5+ years of experience in data engineering or a related field.
• 2+ years of experience working with Azure data service
• Proficiency in Azure data services, including Azure Data Factory, Azure Synapse Analytics (formerly SQL Data Warehouse), Azure Databricks, and Azure Data Lake.
• Strong SQL skills and experience with relational databases.
• Experience with ETL tools and data integration processes.
• Knowledge of data modeling and database design.
• Familiarity with big data technologies such as Apache Spark, Hadoop, or similar.
• Proficiency in programming languages such as Python, Scala, or Java.
• Experience with version control systems, CI/CD pipelines, and Azure DevOps.
• Knowledge of data security and compliance best practices.
• Strong analytical and problem-solving abilities.
• Excellent communication and collaboration skills.
• Ability to manage multiple tasks and priorities in a fast-paced environment.
• A detail-oriented and proactive approach to work.
• Experience with data visualization tools such as Power BI.
• Familiarity with data governance frameworks.
• Experience in industries with complex data requirements, such as finance, healthcare, or e-commerce.
• Knowledge of machine learning and AI concepts.

Certifications

• Azure certifications such as Azure Data Engineer Associate or Azure Solutions Architect.