Overview

Generative AI Engineer – BFSI Domain

Responsibilities

• Design and fine-tune LLMs (Large Language Models) for BFSI use-cases: intelligent document processing, report generation, chatbots, advisory tools.
• Evaluate and apply prompt engineering, retrieval-augmented generation (RAG), and fine-tuning methods.
• Implement safeguards, red-teaming, and audit mechanisms for LLM usage in BFSI.
• Work with data privacy, legal, and compliance teams to align GenAI outputs with industry regulations.
• Collaborate with enterprise architects to integrate GenAI into existing digital platforms.

Qualifications

• 3–5 years in AI/ML; 1–3 years hands-on in GenAI/LLM-based solutions.
• BFSI-specific experience in document processing, regulatory reporting, or virtual agents using GenAI is highly preferred.
• Exposure to prompt safety, model alignment, and RAG pipelines is critical.

Essential skills

Tech Stack

• LLMs: GPT (OpenAI), Claude, LLaMA, Mistral, Falcon
• Tools: LangChain, LlamaIndex, Pinecone, Weaviate
• Frameworks: Transformers (Hugging Face), PEFT, DeepSpeed
• APIs: OpenAI, Cohere, Anthropic, Azure OpenAI
• Cloud: GCP GenAI Studio, GCP Vertex AI
• Others: Prompt engineering, RAG, vector databases, role-based guardrails

Experience

• 3–5 years in AI/ML; 1–3 years hands-on in GenAI/LLM-based solutions.