LinkedIn Skills on the Rise 2026: The fastest-growing Engineering skills in Canada

Our annual list of Skills on the Rise in Engineering highlights the five fastest-growing skills that engineers should be investing in to get ahead in today’s world of work. 

As the engineering landscape rapidly evolves, so do the skillsets needed for success. Prompt Engineering takes the top spot, signaling companies’ focus on improving quality and usefulness of AI outputs by guiding models more effectively. Meanwhile, frameworks like Fast API (No. 2) and LangChain (No. 3) show how engineers are building and deploying AI workflows. The ranking uses the same methodology as our Canada Skills on the Rise list, but reflects members within the specific job function versus the entire country. 

And these insights are just the beginning. You can read more about each skill and start honing your expertise through a related LinkedIn Learning course (free for all members until March 23).

Check out the 5 fastest-growing skills in engineering — and join the conversation using #SkillsOnTheRise.

You can read our full methodology at the bottom of this article. This list is based on LinkedIn data and was produced by LinkedIn data scientist Yao Huang in partnership with editors on the LinkedIn News team (Juliette (Faraut) Bell, Sarah McGrath, Emily Bruck and Juliette Schiff). You can also see the Skills on the Rise in Business Development, Finance, Information Technology and Sales.

What it means: Prompt engineering is the process of crafting and optimizing prompts for LLMs or other AI models to get accurate and relevant outputs and ultimately improve overall model performance. 

💡 Learn the fundamentals of prompt engineering (free LinkedIn Learning course until March 23)

What it means: FastAPI is a framework for building web APIs using Python. It’s popular for its speed, high performance and automatic documentation, allowing engineers to build and scale APIs efficiently. 

💡 Learn how to build scalable, secure and efficient APIs (free until March 23)

What it means: LangChain is an open-source framework used to build LLM applications. Engineers can use it to connect LLMs with external data or tools that help models work faster and more accurately. 

💡 Learn how to build an AI agent using LangChain (free until March 23)

What it means: Cross-functional collaboration is communicating and working with members of different teams across an organization — including clearly defining roles and responsibilities and working toward a shared goal. 

💡 Learn how to collaborate effectively across teams (free until March 23)

What it means: Embedded systems engineering is the design and development of software and hardware systems that integrate into larger systems to perform specific tasks. This specialized type of engineering is critical for processes across a variety of functions, like airbags in cars or automation in robotics. 

💡 Learn to analyze and optimize computing systems (free until March 23)

List Methodology

LinkedIn measures the year-over-year growth of skills based on two pillars: skill acquisition and hiring success. Skill acquisition measures the growth of a given skill being added to member profiles. Hiring success measures the growth of a given skill possessed by members who have been hired in the past year. Growth rates for all metrics are measured by comparing LinkedIn data from December 1, 2024 to November 30, 2025 to the same period in the previous year (December 1, 2023 to November 30, 2024). To be ranked, skills must have had sufficient representation and activity volume over the analysis period.

Data is normalized across all skills. Language skills, basic digital literacy skills and overly broad skills are excluded.