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Tier-1 bank brand, metro hiring, and broad GenAI skillset make competition high.
Role demands specialised LLM, RAG, and finance-grounding, reducing industry transferability.
Many mandatory technical requirements and production LLM experience make shortlisting stringent.
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Own the end-to-end development of LLM application services in Python, including prompt strategies, tool/function calling, and workflow orchestration frameworks like LangChain or LangGraph.
Design and implement Retrieval-Augmented Generation (RAG) systems covering document ingestion, embeddings, indexing, retrieval, and re-ranking, with a focus on finance-specific grounding to minimize hallucinations.
Build and maintain API layers for UI and platform integrations with authentication and auditing; establish evaluation and operational practices including LLMOps, testing frameworks, CI/CD, observability, and compliance with security/privacy requirements.
Strong proficiency in Python engineering with clean architecture, testing, packaging, and performance optimization.
Proven experience delivering production-level or advanced PoC LLM applications using major LLM APIs or models (e.g., Claude, GPT, Gemini).
Hands-on experience implementing RAG systems and practical prompt engineering including tool/function calling.
Experience with API frameworks such as FastAPI or Flask, asynchronous programming, cloud-native delivery preferably on GCP including containers, Kubernetes, CI/CD, observability, and secure engineering practices including LLM security mitigations.
Work Experience Required: Not explicitly mentioned in the JD
Experienced in building complex, production-grade LLM applications applying advanced prompt engineering and RAG methodologies in regulated finance environments.
Skilled in integrating AI workflows with platform services and enforcing semantic and operational constraints (e.g., deterministic query generation, schema validation).
Comfortable operating in cloud-native, security-focused development environments with strong collaboration across data and platform teams.