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Metro Bangalore and an attractive AI title increase competition, while LLM specialization and seniority temper it.
Core LLM engineering skills transfer across industries, though finance domain familiarity could be advantageous.
Several mandatory technical skills (Python, LLM frameworks, vector DBs, cloud, CI/CD) but no explicit years filter.
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Design, implement, and deploy production-grade AI agents and workflows using large language models (LLMs) and AI architecture patterns such as RAG and text-to-SQL.
Develop and maintain AI pipelines and integrate AI solutions with cloud platforms like Azure OpenAI and AWS Bedrock, ensuring observability and monitoring for performance and cost control.
Automate model deployment and orchestration using CI/CD pipelines and evaluate and document AI models comprehensively.
Strong proficiency in Python for AI/ML development.
Hands-on experience with at least one AI framework such as LangChain, LangGraph, or CrewAI.
Familiarity with vector databases like Pinecone, Weaviate, ChromaDB, or FAISS for embeddings and retrieval.
Work Experience Required: Not explicitly mentioned in the JD.
Demonstrated expertise in large language model fundamentals, prompt engineering, and AI agent patterns relevant to applied AI engineering.
Experience deploying and managing AI solutions on major cloud platforms (Azure OpenAI, AWS Bedrock) and implementing CI/CD for AI models.
Familiarity with Agile/Scrum development processes and modern software development best practices including Git workflows.