Chain of thought (CoT) prompting is a technique that enhances the capabilities of large language models (LLMs) by guiding them through a structured thought process. With the increasing demand for advanced AI applications, several job opportunities are emerging in this field. Against this backdrop, companies across sectors are seen posting jobs related to chain of thought prompting, finds GlobalData, a leading data and analytics company.

Sherla Sriprada, Business Fundamentals Analyst at GlobalData, comments: “CoT prompting is getting significant interest within the prompt engineering domain. Companies also seem to be realizing the benefits of CoT prompting and its ability to improve the performance of large language models.”

An analysis of GlobalData’s Job Analytics Database reveals that there has been a growing interest among businesses across industries for hiring personnel with hands-on experience on CoT prompting.

FMR LLC’s “Data Intelligence Business Analyst” role involves writing epics and user stories that translate business needs into functional requirements and validate via user testing development phases with hands-on experience on large language models (LLMs), prompt engineering, and chain of thought prompting.

The “Working Student – Prompt Engineer” role by Oviva AG relates to troubleshooting and resolving prompt-related issues to mitigate unpredictability, bias, and hallucination in generative AI model responses by implementing prompt engineering best practices such as few-shot prompting and chain-of-thought prompting, maintaining high standards for prompt quality, testing, documentation, and optimization.

Altana Technologies Inc’s “Principal Machine Learning Engineer” role is to deploy continuously to improve machine learning models powering Altana’s classification, risk screening, network analysis, and entity resolution capabilities with familiarity in prompt engineering and chain-of-thought prompting for LLMs.

The “Senior Data Scientist” role by Linklaters LLP looks at designing and executing rigorous research frameworks to evaluate the performance of NLP and Generative AI solutions in the legal context with expertise in large language models (LLMs) and transformer architectures (e.g. Llama3, Gemini), including advanced prompt engineering (e.g. Chain of Thought prompting, Prompt Chaining, Long Context Window, agentic flows), and fine-tuning (e.g., LoRa, QLoRa).

The “Prompt Engineer – Generative AI” role by Vertiv Holdings Co focuses on creating, editing, and reviewing prompts for various tasks such as text, image or video generation, summarization, sentiment analysis, data analysis to interact effectively with generative AI models to ensure high-quality, relevant, and contextually accurate outputs using prompt engineering best practices such as few shot prompting and chain of thought prompting including prompt quality, prompt testing, prompt documentation, and prompt optimization.

Sriprada concludes: “With the expanding field of AI, especially in language models, numerous career opportunities across various sectors are emphasizing the need for skilled professionals who can harness this advanced prompting technique effectively.”