Cloud Engineering Lead

We are looking for a Cloud Engineer Lead to join our team.

The Engineering Lead is responsible for leading the design, development, delivery, and

operational excellence of a cloud-native enterprise software product running on Microsoft

Azure. This role provides technical leadership to cross-functional engineering teams,

establishes engineering standards and architecture guardrails, and ensures delivery of

scalable, secure, reliable, and AI-enabled solutions.

The Engineering Lead partners closely with Product Management, Solution Architecture,

DevOps, Security, UX, Data, and AI engineering teams to deliver innovative software

capabilities that create measurable business value. The role combines hands-on technical

leadership with people leadership, mentoring, and strategic technology planning

Requirements:

*Bachelor's degree in Computer Science, Software Engineering, Information Technology, or

related field.

• Master's degree preferred.

• 10+ years of professional software development experience.

• 3+ years leading software engineering teams.

• Proven experience delivering enterprise-scale software products.

• Experience operating mission-critical applications in cloud environments.

• Strong proficiency in one or more modern programming languages such as:

◦ C#

◦ Java

◦ TypeScript

◦ Python

Microsoft Azure

DevSecOps

AI & Data

Working knowledge of:

Leadership Competencies

• Experience with API design and microservices architecture.

• Knowledge of modern software design patterns and distributed systems.

• Hands-on experience with Azure services including:

◦ Azure App Services

◦ Azure Functions

◦ Azure Kubernetes Service (AKS)

◦ Azure Container Registry

◦ Azure API Management

◦ Azure Storage

◦ Azure SQL Database

◦ Azure Cosmos DB

◦ Azure Service Bus/Event Grid

◦ Azure Monitor and Application Insights

◦ Azure DevOps and GitHub

• CI/CD automation

• Infrastructure as Code (Terraform, Bicep, ARM)

• Security-by-design principles

• Automated testing and deployment practices

• Cloud observability and monitoring

• Generative AI concepts and architectures

• Large Language Models (LLMs)

• Prompt engineering

• Retrieval-Augmented Generation (RAG)

• AI Agent architectures

• Azure AI Services

• Azure AI Search

• Azure OpenAI Service

• Vector databases and semantic search

• Responsible AI principles and governance

• AI evaluation and monitoring techniques

Join with us!