Description

You will design, test, and optimize prompts for large language models to solve specific business use cases.

This role is on-site.

Responsibilities

• Develop and refine prompting strategies including zero-shot, few-shot, and chain-of-thought techniques.
• Translate business requirements into NLP tasks for data extraction, classification, summarization, and generation.
• Build reusable Python packages and RESTful APIs for prompt-related utilities and applications.
• Conduct rigorous testing and validation to ensure model robustness, accuracy, and ethical outputs.
• Collaborate with data scientists, ML engineers, and stakeholders to design tailored AI solutions.

Required Skills

• 5+ years of technical experience, preferably in financial services or regulated industries.
• Strong Python programming with proficiency in pandas, numpy, and re.
• Hands-on experience with NLP frameworks such as spaCy, NLTK, or HuggingFace Transformers.
• Deep understanding of LLM prompting strategies and application.
• Experience creating custom Python packages and writing comprehensive unit tests.
• Solid grasp of software engineering principles, including OOP, Git/GitHub workflows, and clean code.
• Ability to handle large-scale datasets and data preprocessing for NLP tasks.
• Experience working with non-technical stakeholders to meet functional goals.

Preferred Skills

• Experience with LLMs (OpenAI, Anthropic, Cohere) and model fine-tuning.
• Knowledge of vector databases, embeddings, and RAG systems.
• Exposure to AWS, GCP, or Azure for deploying AI solutions.

Key Skills

Education

Any Graduate