Lead/Senior Software Engineering - AI Solution Engineering

EPAM · Bangalore

Source and collection record

Last observed by our collector: 8 October 2026 at 11:23 pm IST. This is not a manual review or a confirmation from the employer.

Employer requisition: blttne2tnsdwoknu5nh

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Collected role description

We are seeking a Lead/Senior Software Engineer specializing in AI Solution Engineering to design, build, and deploy full-stack LLM-powered AI applications while driving best practices in cloud architecture, coding standards, and responsible AI delivery across enterprise systems. Responsibilities Build full-stack LLM-powered AI applications using Azure (prompt engineering, grounding, RAG) or vector databases Develop APIs/microservices with Python, .NET, or Node and integrate them with UIs and enterprise systems Drive agentic AI development using Azure AI Foundry and Copilot Studio Implement CI/CD pipelines with GitHub Actions or Azure DevOps and manage cloud deployments across AKS, App Service, and Functions Build data and feature pipelines using Azure Data Factory, Synapse, or Databricks and manage embeddings and prompt versioning Deploy models into production and maintain them over time Adhere to coding standards and AI principles by conducting regular health checks, audits, and code reviews to ensure clean, maintainable, production-level code across project teams Requirements 6-14 years of overall IT experience Strong coding skills in Python, C#, and REST/GraphQL APIs, along with experience in testing and code reviews Hands-on expertise in the Azure AI stack, including Azure OpenAI, Azure AI Foundry, and Azure Cognitive Services Familiarity with Azure AI Search, NLP, and Azure ML, along with vector databases such as AI Search vector index, Cosmos DB, or PostgreSQL Experience in agentic development using the Azure AI stack Proficiency in CI/CD with GitHub, branching strategies, and coding standards such as linters, formatters, and PEP8, along with GitHub Actions pipelines Skills in containerization with Docker and deployment to AKS, App Service, or Functions Knowledge of secrets management via Key Vault and Managed Identity, along with RBAC and network security basics Understanding of Responsible AI, privacy, and data security in enterprise settings Nice to have Experience with GitHub Copilot and Microsoft Copilot Studio (Power Platform) Familiarity with PromptFlow, MLflow, Databricks, and Streamlit or React Background in MLOps and/or LLMOps practices Azure certifications (AI-102, AZ-204) Experience working with one of the big cloud environments (e.g. Azure) Knowledge of RAG patterns, prompt design, tool/function calling, embeddings, retrieval, and caching Preferred experience working with Asset projects

Collected experience requirement

6-14 years