Most In-Demand Engineering Specializations Right Now

Mechanical, hardware, and chemical engineers are among the hardest-to-fill/hardest-to-hire roles for climate tech companies, with time-to-fill times longer than even machine learning engineering roles. ClimateTechList teamed up with data scientist/engineer Jason Zou to analyze our dataset of ~60,000 job posts from 900 climate tech companies posted in the last 6 months. Specifically, we found that the time-to-fill for the following roles were: - Sales: 31.9 days - Marketing: 35.9 - Analyst: 36.0 - Design: 38.5 - Data Science: 40.3 - Product Management: 41.5 - Operations: 42 - Electrical Engineer: 47.1 - Software Eng: 48.2 - Machine Learning Eng: 48.3 - Mechanical Eng: 49.0 - Hardware Eng: 50.2 - Chemical Eng: 51.5 Engineering jobs associated with physical production are hard to hire, namely mechanical engineering, hardware engineering, and chemical engineering, all of which take almost 2x as long to fill (50 days) as sales jobs. Even machine learning engineering positions, in high demand from the AI boom, are filled at a slightly faster rate than these 3 positions Possible reasons for this effect - many of these jobs require in-person work, which makes job matching jobs to candidates inherently more difficult - Federal legislation of the last few years- Bipartisan Infrastructure Law, Inflation Reduction Act, CHIPS Act are all driving massive investments into U.S. physical infrastructure and manufacturing. These investments disproportionally require talent with physical-product engineering skills more than software engineering skills. 👉 For more insights on hiring trends by company, country and climate tech vertical, see our latest climate tech hiring trends report here: https://lnkd.in/gpMCaSZ6 #climatetechlist #decarbonization #energytransition #chemicalengineering #mechanicalengineering #hardwareengineering #hiringtrends

If you're in tech, you're sitting on a goldmine right now. While everyone's debating AI job displacement, the engineering sector is quietly becoming the biggest AI beneficiary. The World Economic Forum projects 78 million net new jobs by 2030, and IT and Engineering is leading the charge. This shift is creating entirely new job categories that didn't exist two years ago. Here are five emerging growth areas for IT and Engineering: 1. AI-native product development → AI Product Managers who understand ML lifecycles and enterprise pain points. 2. AIOps infrastructure → MLOps engineers are moving companies from AI experiments to production. Every enterprise needs these skills. 3. AI cybersecurity → Red teamers for LLMs are literally paid to break AI systems.  4. Enterprise data infrastructure → Vector database engineers managing RAG pipelines are helping AI systems access the right information at the right time. 5. Vertical AI specializations → LegalTech AI specialists, FinTech AI analysts, HR tech AI specialists—domain expertise + AI fluency is the new superpower. The numbers back this up: $632 billion in AI spending (including applications, infrastructure, and IT services) by 2028. This will lead to new AI roles in engineering, product, data, and operations to maintain these AI systems. Bottom line: The engineers who adapt fastest will have the most opportunities. In my latest newsletter, I break down exactly how to transition into each of these roles, plus the specific tools and skills that matter most. What AI role are you most curious about? #AI #Engineering #IT #FutureOfWork

La semana pasada hablé de cómo la IA está redefiniendo lo que las empresas esperan de ti y de cuáles son las habilidades que se están revalorizando. (🔗 https://bit.ly/46hHhc9) Hoy vamos al grano: ¿𝐪𝐮𝐞́ 𝐩𝐞𝐫𝐟𝐢𝐥𝐞𝐬 𝐯𝐚𝐧 𝐚 𝐝𝐢𝐬𝐩𝐚𝐫𝐚𝐫 𝐬𝐮 𝐝𝐞𝐦𝐚𝐧𝐝𝐚 𝐝𝐞 𝐚𝐪𝐮𝐢́ 𝐚 𝟐𝟎𝟑𝟎? 👉 Spoiler: Los que dominan datos, IA y automatización. Según el Future of Jobs Report 2025, estos son los roles con mayor crecimiento: • Big Data Specialists → +110%. La IA solo funciona con datos limpios, gobernados y accesibles. • FinTech Engineers → +95%. Porque cada vez más servicios financieros (pagos, préstamos, seguros, inversión,etc.) se construyen como productos digitales impulsados por IA, datos y cloud. • AI/ML Specialists → +85%. Ya no basta con usar modelos: toca entrenarlos, ajustarlos y ponerlos a trabajar. • Software Developers → +60%. Hay que conectar sistemas, integrar IA, escalar infraestructuras y traducir negocio en soluciones. • Ciberseguridad y gestión de riesgos → +40–55%. La IA abre nuevas puertas… y nuevas amenazas. Se necesitan expertos que lo controlen. En definitiva, las empresas buscan profesionales capaces de entender el reto técnico y, sobre todo, que tengan un impacto directo en el negocio. ------------------------------------------------------------------------------------ Last week, I shared how AI is changing what companies expect from you and which skills are becoming more valuable. (🔗 https://bit.ly/46hHhc9) Today, let’s keep it simple: 𝐖𝐡𝐢𝐜𝐡 𝐫𝐨𝐥𝐞𝐬 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐢𝐧 𝐡𝐢𝐠𝐡𝐞𝐬𝐭 𝐝𝐞𝐦𝐚𝐧𝐝 𝐛𝐲 𝟐𝟎𝟑𝟎? 👉 Spoiler: The ones focused on data, AI, and automation. According to the #FutureOfJobs Report 2025, these are the fastest-growing roles: • Big Data Specialists → +110%. AI only works with clean, reliable, and accessible data. • FinTech Engineers → +95%. More financial services—such as payments, lending, insurance, and investing—are being developed as digital products powered by AI, data, and cloud technology. • AI and Machine Learning Specialists → +85%. It is not just about using models anymore. Companies need people who can train, fine-tune, and implement their strategies. • Software Developers → +60%. They are key to connecting systems, integrating AI, scaling infrastructure, and turning business needs into working solutions. • Cybersecurity and Risk Management → +40 to 55%. AI creates new opportunities, but also new threats. Companies need experts to stay ahead of both. Ultimately, companies seek professionals who understand the technical challenges and, most importantly, know how to create a tangible business impact. #TechTrends #AI #FutureOfWork