Lead System Engineer - Microsoft Azure

EPAM Systems; Hyderabad; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

EPAM Systems in Hyderabad seeks a Lead Cloud Engineer to design enterprise Azure platforms enhanced with Generative AI and agentic workflows. You will set cloud architecture direction, guide DevOps evolution, and partner with leadership to enable secure, scalable systems across regions.

You will oversee multi-region designs, establish CI/CD standards, IaC practices, and governance. The role requires strong English communication and a track record of delivering large-scale enterprise systems from

Qualifications

• 8+ years in cloud engineering and architecture.
• Leadership experience guiding DevOps and platform teams.
• Proven ability to design enterprise Azure solutions with AI capabilities.

Responsibilities

• Design comprehensive cloud and AI solutions on Azure for enterprise strategies.
• Lead multi-region, highly available system designs with DR and failover.
• Guide DevOps transformation and CI/CD, IaC, and security governance.
• Drive AI adoption across business units with production-ready implementations.
• Collaborate with executives and engineering groups to translate business needs into technical blueprints.
• Provide architectural input, code reviews, and mentorship to engineering teams.

Skills

Leadership

Architectural vision

Stakeholder management

Cloud strategy

English communication

Tools

Microsoft Azure

AKS

Docker

Terraform

Bicep

ARM templates

Azure AI Foundry

OpenAI / Claude integrations

Semantic Kernel

LangChain/LangGraph

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)