Lead System Engineer - Microsoft Azure

EPAM Systems; Maharashtra; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

EPAM Systems in Maharashtra is seeking a Lead Cloud Engineer to architect and champion Azure-based platforms with advanced AI capabilities. You will lead cloud strategy, guide DevOps evolution, and drive enterprise-grade, secure, scalable systems across regions.

The role requires deep Azure expertise, strong leadership, and experience with Generative AI, LLMs, and RAG concepts. You will collaborate with executives and engineering teams to deliver AI-powered business value.

Qualifications

• 8+ years in cloud engineering, systems architecture, and delivering large-scale platforms.
• At least 1 year in a leadership capacity.
• Expert-level Azure coverage across compute, storage, identity, networking, and platform services.
• Extensive Kubernetes, AKS, and Docker in production environments.
• Advanced understanding of cloud networking, security, and governance at enterprise scale.
• Infrastructure as Code using Terraform, Bicep, and ARM templates.
• DevOps maturity frameworks and platform engineering that supports self-service development.
• Windows and Linux administration with automation scripting.
• Strong grasp of Generative AI, Agentic AI, and Agentic Workflows.
• Experience with Retrieval-Augmented Generation (RAG), vector DBs, embeddings, and prompt engineering.
• Direct experience with Azure AI Foundry and LLM integrations (OpenAI/Claude).
• Familiarity with AI orchestration tools like Semantic Kernel, LangChain, LangGraph, CrewAI.
• Proven leadership and ability to progress large-scale enterprise systems end-to-end.
• Fluent English communication (B2 level or higher).

Responsibilities

• Design cloud and AI solutions on Azure aligned with enterprise strategy and compliance.
• Ensure multi-region, secure, scalable systems powering critical operations.
• Lead DevOps transformation and modern platform engineering initiatives.
• Define CI/CD, IaC, security controls, and governance standards across teams.
• Develop high-availability designs with DR, failover, and performance tuning.
• Identify and drive AI use cases from concept to production.
• Architect enterprise-scale Generative AI platforms with LLMs and retrieval augmented generation.
• Shape AI strategy with leadership on roadmaps and tool adoption.
• Foster innovation through PoCs, assessments, and new cloud/AI capabilities.
• Translate business needs into practical technical blueprints; provide architectural guidance.

Skills

Azure Cloud

Kubernetes

Terraform

CI/CD

Linux/Windows

AI fundamentals

LLM integration

Tools

AKS

Docker

Bicep

ARM templates

Job description

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)