Back to SearchLead System Engineer - Microsoft Azure with Gen AI
Office in India: Pune, & 5 others
Microsoft Azure& 9 others
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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.
In this position, you'll operate as a technical authority tasked with defining cloud architecture direction, guiding DevOps and platform engineering evolution, and pioneering the introduction of next-generation AI capabilities organization-wide. You'll partner closely with executive leadership, engineering groups, and business units to build secure, scalable, resilient systems supporting critical operations and unlocking fresh AI-powered business potential.
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
Requirements
- 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)