Solution Architect - Azure with AI

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

Job summary

EPAM Systems is seeking an experienced Solution Architect – Azure to lead the design and delivery of scalable AI-driven solutions. The ideal candidate should possess deep technical expertise and strong leadership skills.

Responsibilities include providing technical leadership, collaborating with stakeholders, and designing architecture blueprints for Generative AI platforms. Candidates should have 12–16 years of experience in software engineering with a strong background in Azure cloud and Generative AI.

Qualifications

• 12–16 years of experience in software engineering.
• Expertise in designing and building scalable applications on Azure cloud.
• Hands-on experience with Generative AI solutions.
• Proficiency in Infrastructure as Code (IaC) using Bicep or ARM templates.
• Solid programming skills in Python or C#/.NET.

Responsibilities

• Provide end-to-end technical leadership from solution design to implementation.
• Collaborate with Product Managers to refine user stories.
• Design and develop architecture blueprints for GenAI platforms.
• Lead the development and deployment of AI automation solutions.
• Implement best practices for performance, scalability, and security.

Skills

Azure cloud applications design

Generative AI solutions

Infrastructure as Code (IaC)

Python or C#/.NET programming

Data pipeline design

DevOps practices

Job description

We are seeking an experienced Solution Architect – Azure with AI to lead the design and delivery of scalable, AI‑driven solutions within the Azure ecosystem. The ideal candidate will bring deep technical expertise, strong leadership skills, and a passion for building innovative GenAI platforms that align with business goals and long‑term architecture strategy.

Responsibilities

• Provide end‑to‑end technical leadership from solution design to implementation, ensuring alignment with business goals and long‑term architecture strategy.
• Collaborate closely with Product Managers and stakeholders to refine user stories and translate business requirements into scalable AI‑driven solutions.
• Design and develop architecture blueprints, including system design, integration strategies, and solution components for GenAI platforms.
• Lead the development and deployment of RAG‑based applications, AI automation solutions, and intelligent interfaces within the Azure ecosystem.
• Define and implement best practices for performance, scalability, security, and cost optimization across AI and cloud solutions.
• Guide and mentor engineering teams, ensuring high‑quality code, adherence to standards, and effective delivery.
• Drive integration with enterprise systems using APIs, Microsoft Graph, and other external services.
• Contribute to technical decision‑making, risk assessment, and mitigation strategies while ensuring successful delivery of complex AI solutions.

Requirements

• 12–16 years of experience in software engineering.
• Expertise in designing and building scalable applications on Azure cloud using Azure Functions, Web Apps, API Management, and Azure DevOps.
• Hands‑on experience with Generative AI solutions including Azure OpenAI, prompt engineering and implementation of Retrieval Augmented Generation (RAG) using Azure AI Search.
• Background in building and integrating AI‑driven applications such as chatbots, automation workflows and NLP‑based systems.
• Proficiency in Infrastructure as Code (IaC) using Bicep or ARM templates, along with strong understanding of CI/CD pipelines and DevOps practices.
• Solid programming skills in Python or C#/.NET with exposure to frameworks like FastAPI or Web APIs.
• Competency in designing unstructured data pipelines including data ingestion, transformation, enrichment and indexing for AI‑driven applications.
• Understanding of distributed system design, scalability, performance optimization and monitoring using Azure Application Insights.
• Familiarity with agentic frameworks, orchestration tools (e.g., LangChain, Semantic Kernel) or multi‑agent systems.
• Nice to have: Experience with Kubernetes or container‑based deployments (AKS).
• Nice to have: Exposure to multi‑region deployments and high‑availability architecture.
• Nice to have: Familiarity with SonarCloud or similar code quality tools.
• Background in product‑based or platform engineering environments.