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Mid-level generative AI role, metro location, broad skillset, high applicant density.
Generative AI and MLOps skills transfer across industries, though BFSI preference adds moderate domain bias.
Explicit 6+ years requirement and many mandatory LLM, cloud, and MLOps skills make shortlisting highly strict.
Design, develop, and deploy end-to-end Generative AI solutions using LLMs, RAG pipelines, and AI Agent frameworks.
Develop and manage scalable AI APIs, microservices, vector databases, and semantic search within cloud environments (Azure, AWS).
Implement AI guardrails, monitoring, governance, and collaborate with DevOps/MLOps teams for AI model lifecycle management.
6+ years of experience in AI/Generative AI engineering.
Strong Python development skills and expertise in Generative AI, LLMs, NLP, Transformers, prompt engineering, and RAG architecture.
Experience with cloud platforms Azure and/or AWS, including Azure OpenAI, AWS Bedrock, and related AI services.
Proficiency with vector databases, REST APIs, Docker, Kubernetes, CI/CD, SQL/NoSQL databases, and AI governance practices.
Experienced in building enterprise-scale Generative AI solutions including AI Agents and multi-agent systems.
Familiar with AI ecosystems such as LangChain, LangGraph, Hugging Face, and Model Context Protocol, indicating readiness to work with cutting-edge AI frameworks.
Preferred background in BFSI domain and understanding of AI application security, compliance, and governance requirements.