10 Engineering Skills In India To Invest In 2025: LinkedIn’s Top Picks – News18

Last Updated:March 27, 2025, 09:21 IST

As AI becomes more integral to engineering, AI literacy is now an essential skill and Engineers are required to understand its application across industries.

The world is evolving at an unprecedented pace in the third decade of the 21st century, and with this rapid change, the nature of jobs and the skills required for emerging roles are also transforming. At the dawn of this century, engineering had only a few broad branches, but with the rise of digital technologies and the widespread adoption of artificial intelligence, engineering is now becoming increasingly specialised to meet the demands of a tech-driven world.

With the digital age driving rapid technological advancements, LinkedIn has revealed the fastest-growing engineering skills that will shape India’s job market. The study analysed which skills were most frequently added to professional profiles and in demand by employers. Explore the top 10 engineering skills, as highlighted in LinkedIn’s Skill On The Rise 2025 report, to upskill and stay ahead in an ever-evolving industry.

Large Language Models (LLM)

At the forefront of AI innovation, the development and application of Large Language Models (LLM) such as GPT and BERT are set to transform how we interact with technology. These AI-driven models are powering chatbots, search engines, and content generation tools. Engineers skilled in LLM development will be experts in deep learning, neural networks, and data preprocessing, making this a must-have skill for those aiming to thrive in AI-driven industries.

AI Literacy

As AI becomes more integral to engineering, AI literacy is now an essential skill. Engineers must understand how AI works, its ethical implications, and its applications across industries. Gaining knowledge in AI literacy allows engineers to navigate model interpretability, bias mitigation, and regulatory considerations, enabling them to use AI systems responsibly and effectively.

Prompt Engineering

With the growing prevalence of AI-powered tools, prompt engineering has emerged as a vital skill. This involves crafting precise inputs to guide AI models, ensuring they produce the most relevant outputs. Engineers with expertise in prompt engineering will be adept at optimising AI responses for diverse applications, from customer service to content creation and automation, making them indispensable in the rapidly expanding AI sector.

Code Review

Code review is essential for maintaining the quality, security, and efficiency of software. Engineers proficient in code review are skilled at identifying vulnerabilities, enforcing coding standards, and enhancing collaboration within development teams. This skill ensures that developers—whether junior or senior—write clean, maintainable code that meets industry standards.

Software Design

Despite the rapid evolution of technology, software design remains a fundamental pillar of engineering. As user expectations grow and applications become increasingly complex, architects must design systems that are not only scalable but also maintainable and efficient. Learning the intricacies of software design, including system architecture principles and object-oriented programming, is crucial for engineers who wish to create innovative solutions for today’s demands.

Technical Documentation

Technical documentation is a crucial yet often overlooked skill. Effective documentation ensures clarity in product development, API integration, and software maintenance. Engineers who excel in this area can produce clear, concise manuals, API documentation, and internal guides that improve collaboration and user experience. Mastering this skill is a valuable asset, particularly in large, complex projects.

PyTorch

PyTorch, a deep learning framework, has quickly become a favourite among AI and machine learning engineers. Known for its flexibility and ease of use, PyTorch is ideal for rapid prototyping and model training. Engineers proficient in PyTorch will be well-equipped to contribute to AI research and industrial applications, making it an essential skill for anyone pursuing a career in AI or machine learning.

Optimization

From machine learning to operations research, optimization is a key skill that spans many engineering disciplines. Engineers skilled in optimization techniques can improve system performance, reduce computational costs, and enhance the efficiency of AI models. Mastery in this area will equip engineers to tackle complex problems and provide solutions that are both effective and cost-efficient.

Systems Design

Designing large-scale, distributed systems requires a strategic understanding of architecture, scalability, and fault tolerance. Systems design skills are vital for engineers tasked with creating complex applications that meet high performance and reliability standards. Courses in systems design focus on microservices, API development, and cloud computing strategies, preparing engineers for leadership roles in technology.

Jupyter

Jupyter Notebooks are essential tools for engineers in data science, AI, and research. This interactive environment allows for seamless coding, data analysis, and visualisation in Python. Engineers proficient in Jupyter will be able to test models efficiently, collaborate on projects, and present their findings in a user-friendly format, making it a key skill for anyone working in data-driven roles.