Lead System Engineer - Microsoft Azure with Gen AI

EPAM Systems; India; On-site; INR 2,500,000 - 3,500,000; Full time

Job summary

EPAM Systems is hiring a Lead Cloud Engineer in India to design and build enterprise-scale Microsoft Azure platforms with integrated AI capabilities. The role involves driving cloud architecture strategy, leading transformations, and collaborating with stakeholders to deliver resilient systems.

Candidates must have extensive experience in cloud engineering, particularly with Microsoft Azure and Kubernetes, along with leadership skills. This position offers an opportunity to pioneer the adoption of next-generation AI technologies.

Qualifications

• 8+ years of progressive experience in cloud engineering and platform delivery.
• At least 1 year of relevant leadership experience.
• Expert-level proficiency in Microsoft Azure.

Responsibilities

• Architect cloud and AI solutions on Azure.
• Design scalable, secure, and resilient systems.
• Lead DevOps transformation initiatives.
• Define best practices for CI/CD pipelines.
• Develop multi-region, high-availability architectures.
• Spearhead AI-driven solutions adoption.
• Mentor and guide engineering teams.

Skills

Cloud Engineering

Microsoft Azure

Kubernetes

Docker

DevOps

Generative AI

Infrastructure as code with Terraform

CI/CD pipelines

Scripting languages for automation

AI orchestration frameworks

Job description

Overview

We are hiring a Lead Cloud Engineer to design, build, and drive enterprise‑scale Microsoft Azure platforms with deeply integrated AI capabilities, including advanced Generative AI and Agentic AI solutions. In this role, you will serve as a technical authority responsible for shaping cloud architecture strategy, leading DevOps and platform engineering transformations, and pioneering the adoption of next‑generation AI technologies across the organization. You will collaborate closely with executive stakeholders, engineering teams, and business units to deliver secure, scalable, and resilient systems that power mission‑critical workloads and unlock new AI‑driven business value.

Responsibilities

• Architect end‑to‑end cloud and AI solutions on Azure, ensuring alignment with enterprise strategy, compliance standards, and long‑term scalability goals.
• Design highly scalable, secure, and resilient systems capable of supporting mission‑critical workloads across multiple business units and geographies.
• Lead DevOps transformation initiatives and establish modern platform engineering practices that improve developer productivity and operational efficiency.
• Define and enforce best practices for CI/CD pipelines, infrastructure as code, security controls, and governance frameworks across the engineering organization.
• Develop multi‑region, high‑availability architectures with robust disaster recovery, failover strategies, and performance optimization.
• Spearhead the adoption of AI‑driven solutions across business units by identifying high‑impact use cases and guiding implementation from concept to production.
• Design and deliver enterprise‑grade Generative AI platforms, integrating LLMs, agentic workflows, and retrieval‑augmented generation capabilities at scale.
• Drive AI strategy and adoption by partnering with leadership to define roadmaps, evaluate emerging tools, and align AI investments with business outcomes.
• Foster a culture of innovation through proof‑of‑concept initiatives, technology evaluations, and the introduction of emerging cloud and AI technologies.
• Collaborate with stakeholders, architects, and leadership teams to translate complex business requirements into actionable technical designs.
• Mentor and guide engineering teams, providing technical leadership, code reviews, and architectural guidance to elevate overall team capability.
• Own the lifecycle of large‑scale enterprise systems, including design, deployment, monitoring, optimization, and continuous improvement.

Qualifications

• 8+ years of progressive experience in cloud engineering, systems architecture, and large‑scale platform delivery.
• At least 1 year of relevant leadership experience.
• Expert‑level proficiency in Microsoft Azure, including compute, storage, identity, networking, and platform services.
• Deep expertise in Kubernetes, Azure Kubernetes Service (AKS), and Docker container orchestration for production workloads.
• Advanced knowledge of cloud networking, security architecture, and governance frameworks across enterprise environments.
• Skills in large‑scale infrastructure as code design and implementation using Terraform, Bicep, and ARM templates.
• Background in DevOps maturity models, CI/CD pipeline design, and platform engineering practices that enable self‑service developer experiences.
• Competency in OS administration across Windows and Linux environments, along with proficiency in scripting languages for automation.
• Expertise in Generative AI fundamentals, Agentic AI concepts (multi‑agent systems, orchestration), and agentic workflows for enterprise use cases.
• Understanding of Retrieval‑Augmented Generation (RAG) architectures at scale, including vector databases, embeddings, and prompt engineering.
• Hands‑on experience with Azure AI Foundry and LLM integrations such as OpenAI and Claude for production‑grade applications.
• Familiarity with AI orchestration frameworks, including Semantic Kernel (preferred), LangChain/LangGraph, and CrewAI.
• Strong architecture and leadership skills with a proven track record of owning and evolving large‑scale enterprise systems end‑to‑end.
• Proficient communication skills in English (B2 level or higher).