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
Responsibilities:
*Technical Leadership
*Product Delivery
*Cloud Engineering & Operations Own the overall technical delivery of one or more product domains.
*Lead architecture and design decisions for cloud-native solutions running on Microsoft
Azure.
*Ensure adherence to engineering standards, security requirements, and enterprise
architecture principles.
*Drive software quality through code reviews, design reviews, testing strategies, and
engineering best practices. Provide technical guidance and mentorship to development teams.
Collaborate with Product Managers and Architects to translate business requirements into
scalable technical solutions. Lead sprint planning, backlog refinement, estimation, and execution activities. Identify and mitigate technical risks and delivery dependencies. Drive successful delivery of product releases while balancing quality, cost, and schedule.
Lead development of microservices, APIs, event-driven architectures, and distributed
systems. Ensure solutions are designed for reliability, availability, scalability, and observability. Partner with DevOps teams to implement CI/CD pipelines and infrastructure automation. Monitor platform health, performance, security, and operational metrics.
AI and Intelligent Solutions
*Team Leadership
*Stakeholder Management Drive adoption of AI capabilities within products and engineering practices.
Evaluate opportunities to leverage Generative AI, AI Agents, Retrieval-Augmented
Generation (RAG), Copilot technologies, and machine learning services.
Guide implementation of Azure AI services, agent frameworks, vector databases, AI
search, and intelligent workflow automation.
Establish responsible AI practices including governance, security, transparency, testing,
and compliance.
Promote AI-assisted engineering practices to improve developer productivity and
software quality. Build, mentor, and develop high-performing engineering teams. Foster a culture of accountability, innovation, collaboration, and continuous improvement. Support hiring, onboarding, performance development, and career growth of engineers. Encourage knowledge sharing and engineering excellence across teams. Partner with business stakeholders, product leaders, and technology leadership. Communicate technical direction, delivery plans, risks, and status effectively. Influence strategic technology decisions and roadmap planning.
Requirements:
*Bachelors degree in Computer Science, Software Engineering, Information Technology, or
related field. Masters 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!
