Lead System Engineer - Microsoft Azure

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

Job summary

EPAM Systems in Bengaluru seeks a Lead Cloud Engineer to architect and implement enterprise Azure platforms enriched with Generative AI capabilities. You will act as a technical authority, defining cloud direction, guiding DevOps and platform teams, and driving AI initiatives across the organization.

You will design multi-region, secure, scalable systems, lead IaC and CI/CD standards, and partner with leadership to align AI investments with business outcomes.

Qualifications

• 8+ years in cloud engineering and platform architecture.
• Minimum 1 year in a leadership role.
• Azure expertise across compute, storage, identity, networking, and services.
• Extensive Kubernetes/AKS and Docker production experience.
• IaC design with Terraform, Bicep, and ARM templates.
• DevOps maturity, CI/CD pipeline architecture, and platform engineering.
• Windows and Linux scripting for automation.
• Strong English communication (B2+).

Responsibilities

• Design Azure-based cloud and AI solutions aligned to enterprise needs.
• Build multi-region, high-availability systems for mission-critical operations.
• Guide DevOps transformation and platform engineering practices.
• Enforce CI/CD, Infrastructure as Code, security controls, and governance.
• Develop disaster recovery, failover, and performance tuning strategies.
• Lead AI adoption, identify use cases, and drive production deployments.
• Build Generative AI platforms with LLMs, agentic workflows, and RAG integration.
• Shape AI strategy with leadership to roadmap AI investments.
• Promote innovation via PoCs, assessments, and new tools.
• Translate complex business needs into practical technical blueprints.
• Mentor engineers and provide architectural input to raise capabilities.
• Own end-to-end lifecycle of enterprise systems.

Skills

Azure architecture

Generative AI

Kubernetes/AKS

Terraform/IaC

CI/CD pipelines

Security & governance

Leadership experience

Windows/Linux scripting

Retrieval-Augmented Generation

AI integration (OpenAI/Claude)

Tools

Kubernetes

AKS

Docker

Terraform

Bicep

ARM templates

Semantic Kernel

LangChain

LangGraph

CrewAI

OpenAI

Claude

Vector DB

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)