Responsible for implementing, managing, securing, and supporting IT infrastructure and Cloud Operations across Cyncly’s global environment.
Responsibilities
Deploy, configure, and administer Azure virtual machines, managed disks, availability configurations, and supporting Windows and Linux workloads.
Manage Azure Storage accounts, including Blob Storage and Azure Files, covering access controls, redundancy, lifecycle management, and data protection.
Deploy and support infrastructure-related Azure services, including Azure App Service, Key Vault, Azure Backup, and Azure Site Recovery.
Manage subscriptions, resource groups, resource naming, tagging, and resource lifecycle activities according to organizational standards.
Configure Azure Monitor, Log Analytics, alerts, and diagnostic settings to support availability, troubleshooting, and operational visibility.
Requirements
Bachelor’s degree in computer science, Information Technology, or a related technical field
Senior Platform Engineer focused on data, cloud platform, and networking to build reliable, secure, and scalable data infrastructure on Azure.
Compensation
This position pays between $101,600 – $152,400 based on experience
Responsibilities
Design, build, test, deploy, monitor, and continuously improve scalable data pipelines using Azure Data Factory, Databricks, Apache Spark, and Python.
Implement Delta Lake patterns on Azure Data Lake Storage including table design, schema evolution, Z-ordering, VACUUM, and partition strategies.
Build and maintain event-driven integrations using Azure Service Bus, Event Hub, and Azure Functions.
Provision and manage Azure infrastructure using infrastructure as code (Terraform, Bicep, or ARM templates).
Design and operate Azure-native services including Azure Data Factory, Azure Databricks, Azure Data Lake Storage Gen2, Microsoft Fabric, Azure Key Vault, and Azure Monitor.
Requirements
Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience
As a Technical Solution Architect, become a part of a cross-functional development team engineering experiences of tomorrow, focusing on AI transformation and replacing manual decision-making workflows with reliable, auditable AI-assisted systems.
The Sr Staff AI Security Engineer serves as the primary architect and guardian of the Artificial Intelligence ecosystem, responsible for the end-to-end security of AI architectures specifically within the Azure AI stack.
Compensation
Base Salary Range: $172,780 to $225,720 annually
Responsibilities
Design and implement secure-by-design architectures for the entire AI lifecycle, including data ingestion, model training, fine-tuning, and inference.
Lead the security configuration for Azure OpenAI Studio, Azure AI Foundry, and Azure AI Search.
Develop and deploy security controls, including prompt injection mitigations, rate limiting, and content filtering.
Securely implement and oversee Model Context Protocol (MCP) to facilitate safe communication between AI models and local/remote data sources.
Establish and maintain AI security standards based on global frameworks (e.g., NIST AI RMF, ISO/IEC 42001, OWASP Top 10 for LLMs).
Support the development, testing, and documentation of AI-enabled applications using the Microsoft Azure stack.
Compensation
The hourly rate for this position is based on the level of education at the time the intern program begins: Sophomore $18.00 Junior $22.00 Senior (or May 2028 graduate) $22.00 Current graduate/law student $25.00
Responsibilities
Develop a focused AI solution using Python, REST APIs, Azure SDKs, Azure OpenAI, Azure MCP and Microsoft Foundry.
Assist with prompt engineering, structured outputs, tool calling, AI agents, and retrieval-augmented generation solutions.
Build or support integrations with Azure AI Search, Azure Storage, Azure SQL, Cosmos DB, and approved enterprise APIs.
Prepare and validate approved data for AI use cases, including document chunking, metadata creation, embeddings, and search indexing.
Create unit, integration, and AI evaluation tests covering accuracy, relevance, groundedness, safety, and edge cases.
Requirements
Enrollment in an associate’s, undergraduate or graduate program at a college or university is required. Recent graduates are not eligible for our Developmental Internship program.
Senior Platform Engineer responsible for designing, building, automating, and operating secure cloud platforms in Azure and M365, focusing on AI, data, analytics, and automation capabilities.
Responsibilities
Design and implement complex Azure infrastructure spanning compute, storage, networking, identity, security, and shared platform services
Develop and maintain reference architectures, reusable deployment patterns, and documented technical decisions
Translate business and workload requirements into balanced designs
Engineer version-controlled infrastructure using Terraform and/or Bicep, supported by PowerShell, Azure CLI, or Python
Build and maintain CI/CD pipelines with automated validation, controlled promotion, secure configuration, and recovery procedures
Requirements
Bachelor’s degree in computer science, information technology, engineering, or a related field
Nice to have: Microsoft Certified: DevOps Engineer Expert
Designs and builds cloud-native applications on Microsoft Azure using services such as Azure App Service, Azure Functions, and Azure SQL Managed Instance.
Responsibilities
Designs and builds cloud-native applications on Microsoft Azure using services such as Azure App Service, Azure Functions, and Azure SQL Managed Instance.
Develops scalable, serverless, and event-driven solutions, integrates enterprise systems, and applies CI/CD and security practices.
Build and evolve OrderYOYO’s data platform into a single source of truth for executive reporting, merchant insights, finance automation and AI, leading the move to a modern Microsoft Fabric lakehouse.
Compensation
A salary of up to £80,000 per year (or local equivalent).
Responsibilities
Design, build and operate production-grade data solutions in Microsoft Fabric
Build and run production pipelines in Fabric, Python and PySpark
Design ingestion and transformation patterns that scale across multiple source systems
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