Lead System Engineer - Microsoft Azure with Gen AI

About the Position

We are hiring a Lead System Engineer with expertise in Microsoft Azure and Generative AI to lead cloud architecture strategy and AI adoption.

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

Requirements

• 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)

We Offer

• Opportunity to work on technical challenges that may impact across geographies
• Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications
• Opportunity to share your ideas on international platforms
• Sponsored Tech Talks & Hackathons
• Unlimited access to LinkedIn learning solutions
• Possibility to relocate to any EPAM office for short and long-term projects
• Focused individual development
• Benefit package:
  • Health benefits
  • Retirement benefits
  • Paid time off
  • Flexible benefits
• Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)