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Niche LLM skills reduce pool, but metro Bengaluru and Finastra's recognized fintech brand increase competition.
Core LLM and production AI engineering skills are highly transferable across industries despite fintech context.
Requires specialized LLM, vector DB, cloud deployment and production AI engineering skills, making screening strict.
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Design, implement, and deploy production-grade AI agents using architectures like RAG, text-to-sql, and multi-agent systems integrated into applications.
Develop and maintain AI workflows and pipelines using frameworks such as LangChain or LangGraph, and deploy LLM solutions on cloud platforms like Azure OpenAI or AWS Bedrock.
Implement observability, monitoring, and automation (CI/CD) for AI systems to ensure performance, cost efficiency, and reliability.
Strong proficiency in Python for AI/ML development.
Hands-on experience with at least one AI framework: LangChain, LangGraph, CrewAI, or similar.
Familiarity with vector databases (e.g. Pinecone, Weaviate, ChromaDB, FAISS) for embeddings and retrieval.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in production deployment and integration of large language model (LLM) AI agents.
Skilled in prompt engineering, context engineering, and AI agent patterns relevant to state-of-the-art AI implementations.
Familiar with cloud AI deployment platforms (Azure OpenAI, AWS Bedrock) and CI/CD automation practices.