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Tier-1 brand, mid-level 4–7yr role, Bangalore location, and popular AI engineer title increase competition.
Specialized ML/AI, LLM and cloud skills transfer across industries but require domain-specific experience.
Explicit 4–7 years plus mandatory LLM, LangChain, Python, Azure, and production-readiness requirements raise strictness.
Design, build, integrate, and support production-grade AI applications using LLMs, agentic workflows, RAG, vector search, and Azure cloud services.
Develop and orchestrate AI features and workflows leveraging frameworks like LangChain, LangGraph, and Azure Functions with a focus on scalability, observability, and performance.
Collaborate with MLOps, security, compliance, and platform teams to deliver secure, reliable, and compliant AI solutions and documentation for enterprise use.
4-7 years of work experience in AI/ML engineering or related roles.
Strong proficiency in Python and one backend language (Java or Node.js).
Hands-on experience with production AI integrations involving LLMs, orchestration frameworks, RAG, prompt engineering, LangChain, LangGraph, and Azure cloud deployment.
BTech, MTech, or MBA degree; proficiency with Azure AI Search, vector databases, Redis, Cosmos DB, Azure Functions, and Azure Container Apps.
Deep experience designing and deploying AI solutions at scale using agentic AI frameworks and orchestration in cloud environments, especially Azure.
Ability to integrate AI platforms securely with strong governance, compliance, and production readiness practices.
Proven software engineering background with skills in developing observable, reliable, and maintainable enterprise AI applications.