Overview

We're hiring a Lead Cloud Engineer to build, architect, and champion enterprise-grade Microsoft Azure platforms enriched with sophisticated AI capabilities, spanning advanced Generative AI and Agentic AI solutions.

Responsibilities

• Design comprehensive cloud and AI solutions built on Azure, ensuring they support enterprise strategy, compliance obligations, and sustained scalability
• Build highly resilient, secure, and scalable systems capable of powering mission-critical operations spanning multiple business units and geographic regions
• Guide DevOps transformation efforts and introduce contemporary platform engineering approaches that boost developer output and operational effectiveness
• Establish and enforce standards covering CI/CD pipelines, Infrastructure as Code, security controls, and governance practices across engineering teams
• Build multi-region, high-availability system designs featuring solid disaster recovery planning, failover mechanisms, and performance tuning
• Lead the charge in adopting AI-based solutions across business functions by spotting valuable use cases and steering implementation from initial concept through production
• Build and deliver enterprise-scale Generative AI platforms, incorporating LLMs, agentic workflows, and retrieval-augmented generation at scale
• Shape AI strategy and drive adoption by working with leadership to establish roadmaps, assess new tools, and connect AI investments to business results
• Encourage a spirit of innovation through proof-of-concept work, technology assessments, and introducing emerging cloud and AI capabilities
• Work with stakeholders, architects, and leadership to convert complicated business needs into practical technical blueprints
• Coach and support engineering teams by offering technical direction, participating in code reviews, and providing architectural input to raise team capability
• Take ownership of the full lifecycle for large-scale enterprise systems, covering design, deployment, monitoring, optimization, and ongoing enhancement

Qualifications

• More than 8 years of steadily increasing experience in cloud engineering, systems architecture, and delivering large-scale platforms
• A minimum of 1 year in a relevant leadership capacity
• Expert-level command of Microsoft Azure, spanning compute, storage, identity, networking, and platform services
• Extensive knowledge of Kubernetes, Azure Kubernetes Service (AKS), and Docker-based container orchestration for production environments
• Advanced understanding of cloud networking, security architecture, and governance practices across enterprise-level environments
• Skilled in designing and implementing large-scale Infrastructure as Code using Terraform, Bicep, and ARM templates
• Background in DevOps maturity frameworks, CI/CD pipeline architecture, and platform engineering approaches that support self-service development
• Capability administering both Windows and Linux operating systems, along with scripting skills for automation purposes
• Strong grasp of Generative AI fundamentals, Agentic AI principles (multi-agent systems, orchestration), and Agentic Workflows for enterprise applications
• Understanding of Retrieval-Augmented Generation (RAG) architecture at scale, including vector databases, embeddings, and prompt engineering
• Direct experience with Azure AI Foundry and LLM integrations, such as OpenAI and Claude, for production-level applications
• Familiarity with AI orchestration frameworks, including Semantic Kernel (preferred), LangChain/LangGraph, and CrewAI
• Strong architectural and leadership capabilities, backed by a demonstrated history of owning and advancing large-scale enterprise systems from start to finish
• Solid English communication skills (B2 level or higher)