Lead System Engineer - Microsoft Azure

July 20, 2026

We are hiring a Lead Cloud Engineer to design, build, and drive enterprise-scale Microsoft Azure platforms with deeply integrated AI capabilities, including advanced Generative AI and Agentic AI solutions.In this role, you will serve as a technical authority responsible for shaping cloud architecture strategy, leading DevOps and platform engineering transformations, and pioneering the adoption of next-generation AI technologies across the organization. You will collaborate closely with executive stakeholders, engineering teams, and business units to deliver secure, scalable, and resilient systems that power mission-critical workloads and unlock new AI-driven business value. Responsibilities<ul><li>Architect end-to-end cloud and AI solutions on Azure, ensuring alignment with enterprise strategy, compliance standards, and long-term scalability goals</li><li>Design highly scalable, secure, and resilient systems capable of supporting mission-critical workloads across multiple business units and geographies</li><li>Lead DevOps transformation initiatives and establish modern platform engineering practices that improve developer productivity and operational efficiency</li><li>Define and enforce best practices for CI/CD pipelines, Infrastructure as Code, security controls, and governance frameworks across the engineering organization</li><li>Develop multi-region, high-availability architectures with robust disaster recovery, failover strategies, and performance optimization</li><li>Spearhead the adoption of AI-driven solutions across business units by identifying high-impact use cases and guiding implementation from concept to production</li><li>Design and deliver enterprise-grade Generative AI platforms, integrating LLMs, agentic workflows, and retrieval-augmented generation capabilities at scale</li><li>Drive AI strategy and adoption by partnering with leadership to define roadmaps, evaluate emerging tools, and align AI investments with business outcomes</li><li>Foster a culture of innovation through proof-of-concept initiatives, technology evaluations, and the introduction of emerging cloud and AI technologies</li><li>Collaborate with stakeholders, architects, and leadership teams to translate complex business requirements into actionable technical designs</li><li>Mentor and guide engineering teams, providing technical leadership, code reviews, and architectural guidance to elevate overall team capability</li><li>Own the lifecycle of large-scale enterprise systems, including design, deployment, monitoring, optimization, and continuous improvement</li></ul> Requirements<ul><li>8+ years of progressive experience in cloud engineering, systems architecture, and large-scale platform delivery</li><li>At least 1 year of relevant leadership experience</li><li>Expert-level proficiency in Microsoft Azure, including compute, storage, identity, networking, and platform services</li><li>Deep expertise in Kubernetes, Azure Kubernetes Service (AKS), and Docker container orchestration for production workloads</li><li>Advanced knowledge of cloud networking, security architecture, and governance frameworks across enterprise environments</li><li>Skills in large-scale Infrastructure as Code design and implementation using Terraform, Bicep, and ARM templates</li><li>Background in DevOps maturity models, CI/CD pipeline design, and platform engineering practices that enable self-service developer experiences</li><li>Competency in OS administration across Windows and Linux environments, along with proficiency in scripting languages for automation</li><li>Expertise in Generative AI fundamentals, Agentic AI concepts (multi-agent systems, orchestration), and Agentic Workflows for enterprise use cases</li><li>Understanding of Retrieval-Augmented Generation (RAG) architectures at scale, including vector databases, embeddings, and prompt engineering</li><li>Hands-on experience with Azure AI Foundry and LLM integrations such as OpenAI and Claude for production-grade applications</li><li>Familiarity with AI orchestration frameworks, including Semantic Kernel (preferred), LangChain/LangGraph, and CrewAI</li><li>Strong architecture and leadership skills with a proven track record of owning and evolving large-scale enterprise systems end-to-end</li><li>Proficient communication skills in English (B2 level or higher)</li></ul>