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GenAI specialization and Bangalore location increase applicant density despite mid-tier employer.
Requires GenAI, LLM, and Azure production experience, making cross-industry transfers moderately sensitive.
Explicit 6-8 years, lead requirement, Azure, LLM production and containerization make filters strict.
Develop and deploy AI-enabled applications and services focused on Generative AI using Python-based scalable backends.
Lead the integration of Large Language Models (LLMs) such as OpenAI, Hugging Face, LangChain, or LlamaIndex into enterprise workflows.
Manage production deployment of GenAI solutions on Azure cloud using services like App Service, Azure Functions, Containers, AKS, and implement responsible AI controls and secure integrations.
6-8 years of experience in software/cloud engineering, AI, data engineering, or application development, including 3+ years as a lead developer on enterprise projects.
Strong Python development skills and hands-on experience with Generative AI frameworks and Large Language Models.
Experience deploying applications on Azure cloud platform including services like Azure Functions, AKS, Container Apps, API Management, and security components.
Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or related technical field.
Experienced in delivering production-grade enterprise AI or GenAI solutions including prompt engineering and retrieval-augmented generation (RAG) patterns.
Proficient in building REST APIs, microservices, and containerized applications with Docker and Kubernetes.
Skilled in software architecture principles, AI/ML model lifecycle management, and integrating AI capabilities into enterprise analytics or applications securely with responsible AI practices.