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Niche LLM/Azure specialization reduces candidate pool despite mid-seniority demand and EPAM brand.
High — role requires specialized Azure AI/LLM, vector DB, and agentic AI experience, limiting cross-industry transferability.
High — explicit 6-14 years plus mandatory Azure AI, LLM, CI/CD, containers, and security requirements.
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Design, build, and deploy full-stack LLM-powered AI applications leveraging Azure AI technologies, including agentic AI development using Azure AI Foundry and Copilot Studio.
Develop and integrate APIs/microservices with UIs and enterprise systems, manage cloud deployments on AKS, App Service, and Functions, and implement CI/CD pipelines using GitHub Actions or Azure DevOps.
Ensure adherence to coding standards and Responsible AI principles through regular health checks, audits, and code reviews to maintain clean, maintainable production-level code.
6-14 years of overall IT experience.
Strong coding skills in Python, C#, REST/GraphQL APIs, including experience in testing and code reviews.
Hands-on expertise with Azure AI stack: Azure OpenAI, Azure AI Foundry, Azure Cognitive Services, Azure AI Search, NLP, Azure ML, and vector databases like Cosmos DB or PostgreSQL.
Experience implementing CI/CD pipelines (GitHub Actions or Azure DevOps), containerization (Docker), deployment (AKS, App Service, Functions), and knowledge of secrets management and enterprise security (Key Vault, RBAC).
Senior-level software engineer comfortable leading AI solution engineering projects using full-stack Azure AI services and LLM technologies.
Experienced in cloud-native development and DevOps practices including CI/CD, container orchestration, and cloud security within enterprise contexts.
Familiarity with advanced AI-related tooling and frameworks such as GitHub Copilot, Copilot Studio, MLOps/LLMOps, prompt engineering, and retrieval-augmented generation (RAG) patterns is a plus.