Career Pathways in Technology

When I first stepped into the world of cybersecurity, I was completely lost. I didn’t know where to start, what to learn first, or how people even got into this field. All I knew was—I wanted to be a part of this world where people protect, investigate, and defend against digital threats. 💻⚡ At first, everything looked complicated: hacking, tools, reports, and those mysterious terms like “VAPT” and “SOC.” But slowly, I realized that becoming a cybersecurity professional isn’t about learning everything at once—it’s about building layer by layer. So here’s how the journey begins 👇 📍 Step 1: Build your base Understand the fundamentals — Computer basics, Networking, Linux, Windows, and a bit of Programming. This is your foundation. Without it, cybersecurity concepts won’t make sense. 📍 Step 2: Explore the world of security Learn about Web Security, System Security, Network Security, Cryptography, and Cybersecurity Fundamentals. Then dive deeper into areas like VAPT, Incident Response, Digital Forensics, and Cloud Security. 📍 Step 3: Play and practice This is where learning gets fun! Platforms like TryHackMe, HackTheBox, PortSwigger Academy, OverTheWire, VulnHub, and LetsDefend are your playgrounds. Each challenge you solve teaches you real-world skills. 📍 Step 4: Find your direction You can become a Security Analyst, SOC Technician, Penetration Tester, Threat Intelligence Analyst, or even a Cloud Security Associate ☁️ Each path has its own tools, techniques, and challenges. 📍 Step 5: Prepare for your career Start building projects, upload your reports to GitHub, and prepare at least three pentest reports. Add certifications like CompTIA Security+, CEH, or OSCP. And don’t forget to network on LinkedIn — it opens doors you didn’t even know existed. 🤝 🔥 My advice? Start small, stay consistent, and document everything you learn. Cybersecurity isn’t just about hacking—it’s about protecting, analyzing, and defending. 💪 So if you’re someone who’s confused, just like I was—this roadmap is your compass. Let’s build the next generation of ethical hackers and defenders together. 💣 If you’d like resume guidance, just DM me your “RESUME.” And for more such content, follow my channel: 👉 https://lnkd.in/gGAnR_UF #CyberSecurity #EthicalHacking #InfoSec #TryHackMe #HackTheBox #VAPT #PenTesting #DigitalForensics #SOC #IncidentResponse #BlueTeam #RedTeam #BugBounty #NetworkSecurity #CloudSecurity #Linux #CompTIA #CEH #OSCP #SecurityAnalyst #CyberCareer #CybersecurityCommunity #CyberAwareness #TechCareers #CyberInternship #CyberLearning #InfosecJourney

Europe is investing billions in defense. But one critical gap could hold us back: people. In my latest piece for Fortune, I unpack the growing paradox at the heart of Europe’s defense buildup. While investment in systems, cybersecurity and innovation is accelerating, the talent pipeline is lagging behind.  🛠️ Skilled trades like machinists and technicians are retiring faster than they’re being replaced.  💻 High-tech roles, from AI and cyber to systems engineering, are becoming harder to fill.  📉 Attrition in Europe’s defense sector is now over 4x higher than in the US. The solution isn’t solely more funding - it’s smarter workforce strategy. At Randstad, we see three urgent shifts:   1️⃣ Open up new talent pathways—from adjacent industries to mid-career changers.  2️⃣ Invest in digital upskilling and modern vocational training.  3️⃣ Make defense a career of choice, with purpose, flexibility, and inclusion at its core. Because in the end, no amount of funding can ensure readiness if we don’t have the people to deliver it. Read more in Fortune: https://lnkd.in/eaXqbxQc

If you’re AI-curious but can’t decide where to start, this one’s for you 👇 The AI space is vast. Buzzwords fly. Roles overlap. And it’s easy to get stuck wondering: 👉 Should I become a Data Scientist, ML Engineer, or Product Manager? Instead of chasing titles, map your strengths and figure out where you fit best in the AI lifecycle. 📌 I put together this infographic + a blog post to help you find your lane, with 10 clear roles you can actually train for (even without a PhD or a Stanford badge). 🚀 The 10 Career Paths in AI, Simplified: ➡️ AI/ML Researcher or Scientist – creating new algorithms, publishing papers, pushing the frontier ➡️ Applied ML Scientist / Data Scientist – solving real-world problems with models and experimentation ➡️ ML Engineer / MLOps / Software Engineer (ML) – taking models to production and scaling them ➡️ Data Engineer – building the infrastructure to move and manage data ➡️ Software Engineer – writing core product code with ML components ➡️ Data Analyst – analyzing data to drive insights and business impact ➡️ BI Analyst – working with KPIs, reporting, and decision frameworks ➡️ AI Consultant – advising teams and clients on adopting AI responsibly ➡️ AI Product or Program Manager – aligning AI capabilities with user needs and business goals ➡️ Hybrid Roles – wearing multiple hats across technical and strategic functions 🧭 How to choose the right one for you: → Start with your natural strengths: coding, communication, business thinking, or data sense → Identify the part of the AI lifecycle you enjoy most: research - build - deploy - iterate → Stack the right skills intentionally: • Coders: Python, PyTorch, prompt design, eval frameworks • Data Infra: SQL, Spark, Airflow, Lakehouse, vector DBs • Insights: Analytics, causal reasoning, dashboard tools • Translators: AI roadmap building, governance, storytelling → Focus on shipping evidence of work: demo apps, notebooks, open-source PRs, or experiments → Develop a T-shaped skill profile – go deep in one role, but stay conversational across others 💡 A few truths to keep in mind: → You don’t need to be a “10x coder” to work in AI → Problem-solving > job titles → Projects > perfect resumes → Cross-functional skills are a force multiplier – clear writing, ethical reasoning, and stakeholder empathy go a long way → There’s no “entry-level” in AI – just entry-level impact 📖 Curious to explore deeper? Check out the full blog, and save the infographic to use as a compass for your AI journey: https://lnkd.in/daQNHPyg

Over the last few years, we’ve seen the rise of distinct AI roles: Some focus on building models. Some specialize in prompting them. Some orchestrate entire multi-agent ecosystems. But here’s the challenge: Most people dive into AI without a clear path. They juggle multiple tutorials, frameworks, and buzzwords — without direction. And often feel stuck… despite all the learning. That’s why I created this visual roadmap to demystify what it actually takes to build a successful career in AI—whether you’re starting out, switching domains, or upskilling. 𝟰 𝗥𝗼𝗮𝗱𝗺𝗮𝗽𝘀. 𝟰 𝗖𝗮𝗿𝗲𝗲𝗿 𝗣𝗮𝘁𝗵𝘀. 𝟭 𝗨𝗻𝗶𝗳𝗶𝗲𝗱 𝗩𝗶𝘀𝗶𝗼𝗻 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 Master LangChain, LangGraph, AutoGen, CrewAI Design decision-making agents with memory, context, and orchestration Build truly autonomous multi-agent systems that reason, act, and collaborate 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 Learn the foundations of GenAI: transformers, LLMs, embeddings Build applications using OpenAI, Hugging Face, Cohere, and Anthropic Fine-tune models, use vector databases (RAG), and bring GenAI apps to life 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 Go deep into math, stats, algorithms, feature engineering, and modeling Master Python, Scikit-Learn, XGBoost, and model deployment Build solid ML portfolios that showcase real-world impact 𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 (𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝗔𝗜) Cover it all: computer vision, NLP, reinforcement learning, AI ethics, model governance Use TensorFlow, PyTorch, and integrate AI into products end-to-end Prepares you for both research-driven and production-focused roles What’s unique about this roadmap? Clear step-by-step milestones Specific tooling and frameworks to focus on Career-aligned structure based on real job roles End-to-end guidance from fundamentals to job search Who is this for? College students entering AI Professionals switching to ML or GenAI roles Engineers looking for clarity in a noisy landscape AI educators mentoring the next wave of practitioners Startups guiding their technical talent in AI-first environments This is the kind of map I wish I had when I started. If this helps you or someone in your network: Repost it to reach more learners

Check out these AI Careers and the Skills You Need to Succeed AI is reshaping industries, but breaking into this field means knowing exactly which skills matter for each career path. When working in the AI space, you can choose to analyze data, build models, or design autonomous AI agents. Building an AI skill foundation makes all the difference. 🔹 Data Science: A data scientist blends math, programming, and experimentation. From machine learning algorithms and SQL to big data tools like Spark, the focus is on building predictive models, cleaning complex datasets, and deploying solutions that drive business impact. 🔹 Data Analytics: Data analysts transform raw information into actionable insights. Mastery of Excel, SQL, and data cleaning paired with dashboards (Power BI, Tableau) and data storytelling makes them vital for decision-making and trend analysis in organizations. 🔹 AI Engineering: AI engineers bridge research and production. They work with neural networks, deep learning frameworks (TensorFlow, PyTorch), and advanced fields like NLP, computer vision, and reinforcement learning. Their expertise extends to cloud AI services, pipelines, and scaling models for real-world applications. 🔹 Agentic AI: The newest career track, Agentic AI specialists design autonomous systems. Core skills include prompt engineering, role and agent design, context memory, multi-agent coordination, and tool/API integration. Using frameworks like LangChain and orchestration tools (Make, n8n, Zapier AI), they build AI agents that think, plan, and act. The takeaway you may ask: each AI career path may demands a unique toolkit, however they will most likely remain essential for the next wave of AI innovation. #AI #careers

🚨 Layoffs in the Automotive Industry: What Now? 🚨 The German automotive industry and its suppliers are undergoing another wave of layoffs. If you're an international professional affected by this, don’t panic—your skills are still in high demand. You need to adapt and reposition yourself. The good news? Many industries need your expertise. Here’s how you can transition successfully into new sectors: 🔹 Where Can You Go? ✅ Mechanical & Electrical Engineering – Many manufacturers need engineers with automotive experience. ✅ Renewable Energy & Battery Technology – Transfer your skills to energy storage, hydrogen, and electric mobility. ✅ Aerospace & Defense – Companies like Airbus and Rheinmetall need system engineers and quality specialists. ✅ Rail & Transportation – Rail technology is booming with investments in high-speed trains and public transport. ✅ IT & Software Development – If you worked with embedded systems, cloud computing, or AI, tech companies are hiring. ✅ Logistics & Supply Chain – Your experience in supply chain management, lean production, and operations is valuable. ✅ Wind & Solar Energy – Companies need project managers, engineers, and supply chain experts for offshore & onshore wind farms. ✅ E-Mobility & Charging Infrastructure – The EV market is growing, and charging station providers need technical specialists. ✅ Sustainable Manufacturing – Companies are focusing on eco-friendly production, reducing waste, and improving energy efficiency. ✅ Circular Economy & Recycling – Waste management, battery recycling, and sustainable materials are in demand. 🔹 10 Practical Steps to Reposition Yourself 1️⃣ Rebrand Your Resume & LinkedIn Profile – Highlight transferable skills (project management, quality assurance, process optimization). 2️⃣ Learn the Language of Your Target Industry – Adapt your terminology. Instead of "automotive engineering," use "systems engineering" or "industrial technology." 3️⃣ Expand Your Network Beyond Automotive – Attend events in energy, tech, aerospace, and logistics. Follow industry groups on LinkedIn. 4️⃣ Look at Job Descriptions Outside of Automotive – Identify skills you already have that match other sectors. 5️⃣ Upskill & Certify – Consider PMI, Six Sigma, Agile, or AI & data analytics courses. Many are free online. 6️⃣ Talk to Recruiters Specialized in Other Industries – Don’t just rely on automotive headhunters. 7️⃣ Apply for Internal Transfers – If your company has divisions in energy, industrial automation, or aerospace, explore internal mobility. 8️⃣ Consider Consulting & Freelancing – German SMEs (Mittelstand) often need project-based experts. 9️⃣ Leverage Government Support – Use Jobcenter or Agentur für Arbeit for funding and career coaching. 🔟 Stay Mentally Strong & Proactive – Job searches take time, but with the right strategy, you’ll find your next opportunity. 👉 Your experience is valuable. The key is to position yourself correctly and take action now.

𝗬𝗼𝘂 𝗰𝗮𝗻 𝘀𝗽𝗲𝗻𝗱 𝟰𝟬𝟬 𝗵𝗼𝘂𝗿𝘀 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗔𝗪𝗦 𝗮𝗻𝗱 𝘀𝘁𝗶𝗹𝗹 𝗴𝗲𝘁 𝗶𝗴𝗻𝗼𝗿𝗲𝗱. Here’s why you’re not getting hired, and how to flip the game. Most people treat the cloud like school: 📚 Study. 📝 Test. 🎓 Cert. Then… silence. No job. No calls. No shot. Why? Because you’ve built 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲, not 𝘃𝗮𝗹𝘂𝗲. Here’s what the people who go from “𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴” to $80, $90 or even $100K+ offers actually do (that no course will teach you): 𝟭. 𝗧𝗵𝗲𝘆 𝗕𝘂𝗶𝗹𝗱 “𝗣𝗿𝗼𝗼𝗳 𝗔𝘀𝘀𝗲𝘁𝘀,” 𝗡𝗼𝘁 𝗝𝘂𝘀𝘁 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 Projects are good. But 𝘗𝘳𝘰𝘰𝘧 𝘈𝘴𝘴𝘦𝘵𝘴 are better. This means: ✅ GitHub repo + architecture diagram ✅ Loom walkthrough: "Here’s how I built it & why" ✅ LinkedIn post: “Business impact of my cloud solution” ✅ Resume bullet: “Reduced X by Y using Z” They don’t just 𝘣𝘶𝘪𝘭𝘥 stuff, they 𝘱𝘢𝘤𝘬𝘢𝘨𝘦 it like a portfolio pitch deck. 𝟮. 𝗧𝗵𝗲𝘆 𝗦𝗼𝗹𝘃𝗲 𝗜𝗻𝘃𝗶𝘀𝗶𝗯𝗹𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺𝘀 Most beginners build what’s 𝘰𝘣𝘷𝘪𝘰𝘶𝘴 (launch an EC2, host a static site). The ones that want the offer, build what’s 𝘶𝘯𝘥𝘦𝘳𝘷𝘢𝘭𝘶𝘦𝘥: “Automated IAM cleanup across dev/test accounts” “Created centralized logging using ELK & S3 lifecycle policies” “Built a budget alerting system for sandbox projects” These sound advanced, but they’re not. They just 𝘀𝗼𝗹𝘃𝗲 𝗿𝗲𝗮𝗹 𝗽𝗮𝗶𝗻𝘀 companies actually deal with. 𝟯. 𝗧𝗵𝗲𝘆 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 They don’t just say, 👉🏾 “I set up a VPC.” They say, 👉🏾 “I designed a 3-tier VPC for a fintech app that needed PCI-DSS compliance, public ELB, private app + DB tiers, NAT gateway for secure outbound traffic.” Even if it’s all mock, it 𝘵𝘦𝘭𝘭𝘴 𝘱𝘦𝘰𝘱𝘭𝘦: 🎯 “I think like an engineer.” 🎯 “I understand context.” 🎯 “I can walk into your problem and build something that makes sense.” 𝟰. 𝗧𝗵𝗲𝘆 𝗥𝗲𝘃𝗲𝗿𝘀𝗲-𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗝𝗼𝗯 𝗗𝗲𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝗼𝗻𝘀 Every cloud job is a cheat sheet. Instead of guessing what to build, they: * Pull 10 job posts * Circle every tool/problem mentioned * Build mini-projects around those * Post their journey like a series: “One week, one use case” 👉🏾 By week 5, they’ve built a portfolio targeted to actual market demand. 𝟱. 𝗧𝗵𝗲𝘆 𝗔𝗰𝘁 𝗟𝗶𝗸𝗲 𝗧𝗵𝗲𝘆 𝗔𝗹𝗿𝗲𝗮𝗱𝘆 𝗕𝗲𝗹𝗼𝗻𝗴 This is subtle but massive: They don’t “hope to break in.” They speak, share, and build like they’re already in. Their content doesn’t say: “I’m learning cloud.” It says: “Here’s how I think about cloud architecture.” That energy gets noticed. That mindset 𝗽𝘂𝗹𝗹𝘀 𝗗𝗠𝘀. That shift = leverage to show you can solve THIER problem. Want to Actually Get Hired? Stop going after all certs. Start proving capability. Start showing how you solve problems. 💬 Drop “𝗣𝗥𝗢𝗢𝗙” if you want the full list of value-packed, business-focused projects that actually convert to interviews. I'll send you access to them Let’s make the work, 𝘸𝘰𝘳𝘬 for you.

The cybersecurity certification game has changed dramatically in 2025. After reviewing hundreds of job postings and talking with hiring managers, here's what actually matters now and what's become obsolete. The Big Shifts: Cloud certifications are now commanding 15-20% salary premiums. AWS Security Specialty and Azure Security Engineer aren't optional anymore, they're expected. If you're picking one, follow the money. AWS dominates most markets, but Azure leads in government and enterprise. CISSP remains essential for leadership roles, but timing matters. Early-career professionals with CISSP often get labeled as "title hunters." Save it for when you have 5+ years experience and are eyeing management positions. The surprising winner? Specialized beats generalist every time. Certified Kubernetes Security Specialist (CKS) holders are writing their own tickets. OSCP continues to destroy CEH in market value and employers want proof you can hack, not just talk about it. What's Working by Career Stage: Entry Level: Security+ remains your ticket in. Pair it with cloud fundamentals (AWS/Azure) for maximum impact. Cost: ~$400-600 total. ROI: Excellent. Early Career (1-3 years): Go deep, not broad. SOC analysts need CySA+ or GMON. Future pentesters need OSCP. Skip generalist certifications entirely. Mid-Career (3-7 years): Choose your path. Technical track? Advanced cloud security or DevSecOps certs. Leadership track? Start that CISSP journey. Senior (7+ years): CISSP + business acumen wins. Add CISM for GRC roles or maintain technical edge with architect-level cloud certifications. The Reality Check: CEH is dying. Despite appearing in job posts, hiring managers increasingly view it as outdated. Don't waste your money. SANS certifications are incredible but at $7,000+, calculate carefully. Three specialized certifications might open more doors than one premium cert. AI security certifications are mostly hype. Stick with established providers adding AI modules to existing programs. The certification landscape evolves fast, but the principle remains constant: certifications open doors, skills keep them open. Choose credentials that align with where you're going, not where you've been. What's your certification strategy for 2025? Are you going deep in a specialty or building breadth? #Cybersecurity #Certifications #CareerDevelopment #InfoSec #CloudSecurity #TechCareers

Which Cybersecurity Path is Right for you? With so many pathways and technical jargon, it’s easy to feel lost. The key is finding the path that aligns with your strengths and interests. Here's how 1️⃣ Offensive Security – The Ethical Hackers If you love solving puzzles, figuring out how things work, or finding loopholes in rules, this might be your path. Offensive security professionals think like attackers to identify weaknesses before real hackers do. Roles: Ethical Hacker, Penetration Tester, Red Teamer Key Skills: Curiosity, creativity, and problem-solving 2️⃣ Defensive Security – The Protectors If you enjoy keeping things in order, spotting patterns, or noticing when something feels “off,” defensive security could be a great fit. These professionals monitor systems, investigate suspicious activity, and stop cyber threats in their tracks. Roles: SOC Analyst, Incident Responder Key Skills: Attention to detail, critical thinking, and staying calm under pressure 3️⃣ Governance, Risk & Compliance (GRC) – The Policy Makers If you like planning, making checklists, or ensuring things follow the rules, this is for you. GRC professionals create security policies, ensure companies follow regulations, and assess risks before they become problems. Roles: Risk Analyst, Compliance Officer, Security Auditor etc Key Skills: Organization, communication, and decision-making 4️⃣ Cloud Security – The Future of Defense If you’re fascinated by how apps and websites work behind the scenes, enjoy learning about new technology, or like organizing digital spaces, cloud security might be your lane. These experts secure cloud-based systems that power businesses. Roles: Cloud Security Engineer, Cloud Security Architect Key Skills: Adaptability, curiosity, and troubleshooting 5️⃣ Digital Forensics & Incident Response – The Investigators If you enjoy watching detective shows, solving mysteries, or piecing together clues to uncover a story, this could be your ideal path. Digital forensics professionals analyze cyber incidents to figure out what happened and how to prevent it in the future. Roles: Digital Forensics Analyst, Incident Responder Key Skills: Patience, analytical thinking, and storytelling (yes, telling the story of an attack!) How to Choose the Right Path 1️⃣ What excites you? Are you more of a problem-solver, a protector, a strategist, or an investigator? 2️⃣ What skills do you already have? Think beyond tech—are you naturally detail-oriented, creative, or good at explaining things? 3️⃣ What’s in demand? Cloud security, offensive security, and risk management are hot areas right now. 💡 Cybersecurity isn’t just about hacking—it’s about finding a path that fits your strengths and continuously learning. And if you know someone considering a cybersecurity career, share this post with them! #Cybersecurity #CareerGrowth #TechCareers

I created a Roadmap of 6 Steps to Build a Cybersecurity Career from Scratch. If you are looking to transition into a career that will change your life, this guide will help. One of the first jobs I've had in IT was helping people configure their modems to dial into the internet. Yes, I'm that old. "Back in my day" I used to install operating systems with about 20 floppy disks. Yes, times have changed. I've been lucky enough to stay in this field for over 25+ years. What have I learned? There is more opportunity in tech than most other industries and you can self study your way from start to finish if you have the work ethic. I have developed a Cybersecurity Roadmap for those who want to transition into this field. 1. Research & Identify your Career Path - There are many sectors within cybersecurity that you can learn. Red team, blue team, GRC, AI security, cloud security, and more. Research all of them and find one that really peaks your interest. Ask yourself "Is this something I want to do everyday?" 2. Build Foundational IT Skills through Self Study - Start with the basics. Learn operating systems such as Windows and Linux. Learn networking. For a bonus, learn the Python coding language. 3. Get Entry Level Certifications - There are many certs out there. CompTIA's A+, Network+, or Security+ is a good place to start. You can also look at Google's Cybersecurity Certificate, which is currently on Coursera. 4. Gain Hands on Experience - This one really matters. When I was learning, I built my own labs. I learned networking and how to use VMs just to get my labs setup. Then I'd install different offensive tools and defensive tools to get some hands on. You can also use HacktheBox or TryHackMe if you don't have the resources to build your own labs. Get involved in some CTF (Capture the Flag) events too. 5. Network, Seek Mentorship & Join Communities - As I always say, your network is your net-worth. It really is. Attend meetups, both physically and virtually. Find a mentor and learn. The more people you know, the more opportunity will come your way. 6. Build your Brand and Apply for Roles - This is extremely important. It's not about who you know, it's about who knows you. Share your knowledge with others. Build an outstanding profile that stand out from the rest. Teach others what you have learned. I guarantee you are a step ahead of someone else in their journey. By helping others, it shows your knowledge and builds your network extremely fast. None of these above are easy. However, if you have the work ethic and can buckle up for the journey, there will be opportunity on the other side. If you need help on direction or have questions on any of these, you can find me at https://lnkd.in/g2BR9myb. I'm Mike Miller | vCISO | Appalachia Technologies #cybersecurity #informationsecurity #infosec #careers