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Metro location and reputable fintech brand, but niche LLM skillset limits applicant density.
LLM and AI engineering skills are broadly transferable across industries despite fintech context.
Multiple mandatory LLM, framework, cloud, and deployment skills indicate high shortlisting strictness.
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Design, implement, and deploy production-grade AI agents using large language models and AI architectures such as RAG, text-to-SQL, and multi-agent workflows.
Build and maintain AI workflows, pipelines, and integrations on cloud platforms like Azure OpenAI or AWS Bedrock.
Implement monitoring, observability, and automated deployment (CI/CD) for AI systems to optimize performance, cost, and reliability.
Strong proficiency in Python programming for AI/ML development.
Hands-on experience with AI frameworks such as LangChain, LangGraph, CrewAI, or equivalent.
Knowledge of LLM fundamentals, prompt engineering, context engineering, and AI agent patterns (RAG, text-to-SQL, etc).
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in deploying scalable large language model solutions in production environments with cloud platforms like Azure or AWS.
Demonstrated ability to develop end-to-end AI agent workflows including orchestration and function calling.
Familiar with Agile/Scrum methodologies and collaborative software development practices in fast-paced technology teams.