Top technology companies such as Accenture, IBM, and the Tata Group are hiring artificial intelligence specialists to integrate AI with their core functions. This has led to a demand for “prompt engineers,” a new category of workers skilled in structuring instructions for AI models. In the past six months, 18,000-22,000 new roles have been created, with college graduates filling entry-level positions. Engineers with AI and machine learning certifications can earn around Rs 20 lakh annually, while entry-level prompt engineers earn about Rs 4 lakh per annum.
The demand for AI prompt engineers has surged by 300% year-on-year due to the rapid adoption of generative AI technologies like ChatGPT and DALL-E. Companies are investing in these technologies to enhance their business functions, increasing the need for prompt engineers. However, as AI applications scale, prompt engineering skills may become essential for all stakeholders involved in the AI lifecycle.
Prompt engineering involves creating instructions that generative AI models can understand, requiring knowledge of AI models, natural language processing, programming languages like Python, and strong analytical skills. This skillset is crucial for AI model training, fine-tuning, testing, and deployment. The role is more than just writing sentences; it involves ensuring cost-effective and accurate AI model outputs.
Industry experts predict significant growth in AI prompt engineering jobs in India, with average salaries ranging from Rs 8 lakh to Rs 13 lakh annually. The job market for generative AI in India is expected to grow at a compound annual growth rate of 20% over the next decade. In the US, starting salaries for prompt engineers range from $120,000 to $350,000 per year, reflecting a higher demand due to early adoption of AI technologies.
Prompt engineers play a vital role in integrating AI into applications and designing user-friendly interfaces. For example, AI-powered process automation startup E42.ai developed a tool to generate SWOT reports by crafting precise prompts to extract relevant information from large datasets.
