Senior Prompt Engineer – Banking Domain

Senior Prompt Engineer – Banking Domain

Job Title:

Senior Prompt Engineer – Banking Domain

Location:

New York (Preferred) - Remote is possible Job Type: Full-Time / Contract

Job Description:

• Experience:
  
  6+ years overall, 2+ years in prompt engineering, with strong exposure to banking/financial services

About the Role:

We are seeking a highly skilled Senior Prompt Engineer with deep experience in Large Language Models (LLMs) and a strong understanding of the banking and financial services domain. You will be responsible for designing, developing, and optimizing prompts to enhance AI-driven banking products by collaborating with businesses, ensuring they align with regulatory standards and industry-specific needs.

Key Responsibilities :

• Design, refine, and optimize high-quality prompts for various use cases in the banking sector (e.g., fraud detection, customer service automation, regulatory compliance).
• Collaborate with data scientists, ML engineers, and product teams to integrate prompt-based solutions with LLMs like GPT, Claude, Gemini, etc.
• Translate complex banking processes and regulations into structured prompts for AI understanding and output generation.
• Test and validate prompt performance through iterative experimentation and A/B testing.
• Maintain a strong focus on explainability, accuracy, and risk mitigation in AI-generated responses.
• Ensure compliance with industry regulations (e.g., GDPR, PCI-DSS, Basel, etc.) in prompt-driven outputs.
• Document prompt libraries, workflows, and use case performance metrics.
• Stay current with AI and LLM advancements and their applications in financial services.

Required Skills :

• 2+ years of hands-on experience with prompt engineering using LLMs (OpenAI GPT-4, Claude, LLaMA, etc.)
• 5+ years of strong background or work experience in banking, fintech, or financial services
• Understanding of NLP, transformers, embeddings, and generative AI techniques
• Familiarity with data privacy, security, and regulatory requirements in financial contexts
• Proficiency with tools like Lang Chain, Llama Index, Vector DBs (e.g., Pinecone, FAISS)
• Experience with Python and APIs for AI integration
• Analytical mindset with strong problem-solving and experimentation skills

Preferred Qualifications :

• Experience building RAG (Retrieval-Augmented Generation) pipelines in BFSI contexts
• Knowledge of financial products, KYC/AML workflows, or trading platforms
• Certifications in AI, ML, or finance (e.g., CFA, FRM) are a plus
• Prior experience working with conversational AI in regulated environments