Alternative Career Paths for Developers

Most people think career diversity is career suicide. They're wrong. Single-path careers are the real risk. Emily Jones Joanisse proves it. Programmer. DJ. Nonprofit founder. 2008 crisis killed her Italian tech job. She didn't panic. She had options. Here's how she built a bulletproof career: 1. Build Skills That Travel Anywhere Emily learned programming young. Wrote scripts for her physicist father. Studied computer science. Worked across countries. Crisis hit. Job gone. She pivoted to teaching tech to children. Same core skill. Different stage. Americans change jobs 12 times by age 55 (Bureau of Labor Statistics). Portable skills survive. Specialized roles don't. Your move: What skills transfer anywhere? 2. Keep Your Creative Lane Alive Emily started DJing during her degree. Not a side hustle. A second identity. Canada to Europe. Milan hotel residencies. "It gave me community, confidence, and connection." She built networks her programming job never could. Creative paths open different doors. One-third of Americans ages 25-44 completely changed fields since their first job (edX survey). Your move: What creative outlet could become more? 3. Combine Your Lanes for Unique Impact 2018: Emily co-founded Connected Canadians. Free tech support for seniors. "I saw older adults struggle with digital tools." Teaching experience + programming background = solution nobody else saw. Your intersections create value competitors can't copy. Your move: What problems only your combination can solve? 4. Start Your Second Path Before You Need It Don't wait for the layoffs. Emily built DJing alongside programming. Each path supported the other. When tech crashed, music kept her afloat. When gigs were slow, coding paid the bills. 83% of workers now prioritize work-life balance over pay (High5Test research). They want options. Not just paychecks. Your move: Start exploring while you have security. Range is resilience. Multiple paths don't dilute your career. They bulletproof it. ♻️ Share this with someone stuck in one lane 🔔 Follow Kabir Sehgal for more

🖥️ #SoftwareDevelopers: Ever feel like the job you fought for is quietly disappearing? Regular software dev roles are down 📉20%. 🔴And if you’re still grinding the same way you did in 2023…that role probably won’t exist in 2 years, let alone 20. 📉 🔜Your foundation was cranking out code, and pivoting will allow you to get to higher-value work like #orchestration, strategy, and integration. By 2027, 80% of engineers will need to upskill for new AI-driven roles. 🟢 Here are some pathways you can pivot strategically in 2026 and build upon the skill sets you already possess and integrate your career into the new AI landscape. A lot of this information is taken from PwC’s #AIJobs Barometer: 💵 150-250k range. 💻 1. ML Engineering/AI Automation Specialist This is by far the most direct pivot from SD—move from writing code to building, fine-tuning, and deploying AI systems. Seniors excel here with their experience in production-scale work. 95% of AI pilots fail without proper orchestration, so companies need devs who can bridge LLMs to real workflows (for example: using LangChain/LangGraph for agentic systems). ✅ Your Pivot Point: Learn ML frameworks (PyTorch/TensorFlow), prompt engineering, MLOps. Build a portfolio with agent-based projects. 💻 2. #SystemsArchitecture & Engineering Shift to designing complex, scalable systems where AI handles low-level #code, but you oversee integration, security, and optimization. AI struggles with holistic architectures, so your experience shines in this environment. ✅ Your Pivot Point: Focus on cloud (AWS/Azure), microservices, and AI system design (Example: cascading LLMs for cost optimization). Practice with tools like GitHub Copilot for validation. 💻 3. #Cybersecurity with AI Focus Pivot to AI-cyber roles like threat detection engineers or secure AI architects. AI amps attacks, but also defenses; devs with coding chops are perfect for building agentic security tools. ✅ Your Pivot Point: Certs like CISSP, learn AI vulnerabilities (prompt injections), tools like CrowdStrike’s AI co-pilots. 💻 4. #DataEngineering/Science or Analytics Evolve into handling massive datasets for AI training/inference. AI needs clean, scalable data pipelines, and your dev skills transfer seamlessly. ✅ Your Pivot Point: Master Spark, Kafka, SQL/NoSQL; add ML basics for data prep. 💻 5. Product Management or AI Strategy This is a people skills/people facing role! Leverage domain knowledge to guide AI products. Go from code to roadmaps, user needs, and ethical decisions AI can’t make. ✅ Your Pivot Point: PM certs (PMP), learn AI ethics/governance. Build by collaborating on open-source AI projects. 💻 6. Domain-Specific Pivots (e.g., Space, Healthcare, Fintech) Apply dev skills to specialized verticals where AI integrates but #human oversight rules—example: #spacetech or healthcare AI systems. ✅ Your Pivot Point: Domain certs (e.g., AWS for Space); focus on AI-human teaming. #HappyFriday !

“Do I have to be a software engineer as a CS major?” This is one of the most common questions I get from students like me! The short answer? No. The long answer? Here’s a breakdown of what you can do with a computer science degree beyond just coding. This especially dedicated to cs students who confused about their career paths and told software engineering is the only way Whether you’re an undergrad, a master’s student, or a new graduate, computer science opens up more doors than you might think. If you’re curious, creative, analytical, or business-minded — there’s likely a role for you. Here’s a list of career paths that are just as valuable as software engineering: ✔️ 2. Product Manager (PM) PMs define the what and why of a product. You’ll work closely with engineers, designers, and stakeholders to bring ideas to life. Great for those who enjoy problem-solving, communication, and user-focused thinking. Entry points: APM (Associate Product Manager) programs, startup internships, building your own product. ✔️ 3. Tech Consulting As a consultant, you help organizations solve problems using technology — whether that’s cloud migration, system design, or implementation of enterprise tools. A good fit if you like strategy, working with clients, and adapting quickly. Entry points: campus recruiting, roles at firms like Accenture, Deloitte, or IBM, or tech-focused consulting startups. ✔️ 4. Solutions Engineer / Sales Engineer This is a hybrid role where you explain the technical value of products to clients during the sales cycle. You’ll do demos, answer technical questions, and help integrate tools into complex systems. Entry points: pre-sales engineering roles, internships at B2B SaaS companies, customer engineering pathways. ✔️ 5. AI / Machine Learning Engineer Specialized engineers who build intelligent algorithms for real-world applications — from chatbots to recommendation engines. Strong foundation in math, statistics, and deep learning is key. Entry points: ML research internships, bootcamps, courses in PyTorch, TensorFlow, and real-world datasets. ✔️ 6. Cybersecurity Analyst / Engineer You defend networks and systems against threats, monitor vulnerabilities, and investigate incidents. It’s a high-demand field with growing relevance. Entry points: security certifications (CompTIA Security+, CEH), CTF competitions, internships in IT security You don’t have to be a software engineer. You can be a strategist, a builder, a communicator, a designer, or a researcher. A CS degree is a powerful tool what you build with it is up to you. Ask yourself: What kind of problems excite me? Who do I want to help? What do I want to create? That answer will point you toward the right path. I will be doing a part 2 as I had to cut out a lot in this post or maybe I’ll just make it a new edition for MTD🙃 #ComputerScience #CareerPaths #TechConsulting #ProductManagement #cs #UXDesign #students #Cybersecurity #NewGrad #CSMajors #WomenInTech #TechCareers

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

Everyone wants to code. But the jobs are not enough to go round. You're probably trying to break into tech right now and chances are, you're learning software or web development. From Bootcamps to YouTube to freeCodeCamp to Udemy, on and on. Frontend today. Backend tomorrow. Full stack next week. And still, silence from recruiters. Let me tell you something you're probably already suspecting but haven’t heard clearly: Software and web development are some of the most oversaturated tech roles in Nigeria today. It’s not that they don’t matter. They do. But everyone is chasing them. Thousands of beginner devs. Same projects. Same portfolios. Same roadmap. And the jobs? Just a handful are available (in contrast to those who need them), some already get filled before you even hear about them. But wait, tech isn't just code. And that’s the part nobody’s really explained to you yet. The tech industry is wide. The options are real. And some of the best paths are the quietest ones. Allow me show you a few you might not have considered: ➠Cloud Engineering If you can learn AWS, Azure, or Google Cloud, you're already more useful than most. Businesses are scaling, and they need hands. ➠ DevOps Do you love solving puzzles and making systems run smoother? DevOps is the engine room behind great tech experiences. ➠Cybersecurity Attacks are increasing, but defenders are still few. If you can learn how to protect businesses, you become a serious asset. ➠Data Engineering Everyone wants to be a data scientist. But data engineers—the ones who build the pipelines and prep the data—are in shorter supply and high demand. ➠Technical Product Support / Solutions Engineer You’re good with people and tech? This role lets you bring both strengths to the table. No deep coding, but plenty of impact. ♣️Here’s what I’m saying to you: It’s okay if you started with code. But please, don’t box yourself in just because that’s what everyone else is doing. If tech is a big city. Software development is just like a busy street. (Something about this is making me think of Lagos 😂). Anyways, I'd advice that you take a detour because, you might just find the peace, progress, and opportunities you’ve been chasing all along. What path are you quietly curious about, even if no one around you is talking about it yet? You know the drill, don't keep this gist to yourself, share with someone, Dave for the future and repost for reach. Cheers to you and happy new week.

Being trapped in a job you don't like is soul-sucking. The good news is pivoting is easier than ever. Companies are desperate for specific skills. Here's what many people don't know: 🟢 You don't need another degree 🟢 Many certifications take just weeks 🟢 Your current skills likely transfer I know things seem bleak in the market. But these roles are in demand. Here are 16 high-demand careers you can pivot into: (Want the certification links? ⇢ https://lnkd.in/e5EjDQXZ) 1/ Revenue Operations ↳ Perfect for data-driven problem solvers who love optimizing systems and connecting dots across departments 2/ Supply Chain Analyst ↳ Ideal for detail-oriented planners who thrive on logistics puzzles and making complex systems run smoothly 3/ Robotic Process Developer ↳ Great for tech-curious professionals who get excited about automating repetitive tasks and building efficiency 4/ Sustainability Consultant ↳ Made for purpose-driven individuals who want to help organizations reduce their environmental impact 5/ AI Engineer ↳ Perfect for developers and tech enthusiasts who want to be at the forefront of the AI revolution 6/ Cybersecurity Analyst ↳ Ideal for protective problem-solvers who think like hackers but want to defend against them 7/ Data Scientist ↳ Great for math lovers who enjoy finding patterns in chaos and telling stories with numbers 8/ Project Manager ↳ Perfect for natural leaders who excel at juggling multiple priorities and keeping teams on track 9/ Agile/Scrum Master ↳ Ideal for facilitators who love removing roadblocks and helping teams work more efficiently together 10/ Data Analyst ↳ Made for curious minds who love digging into spreadsheets and turning data into actionable insights 11/ Change Manager ↳ Perfect for empathetic leaders who excel at helping people navigate organizational transitions smoothly 12/ Solutions Architect ↳ Great for big-picture thinkers who enjoy designing complex technical systems that solve business problems 13/ Processes Operator ↳ Ideal for methodical professionals who get satisfaction from streamlining workflows and eliminating waste 14/ Salesforce Admin ↳ Perfect for tech-savvy organizers who love customizing systems to make everyone's job easier 15/ Professional Editor ↳ Made for grammar enthusiasts and word lovers who catch mistakes others miss and polish rough drafts 16/ Prompt Engineer ↳ Ideal for creative communicators who understand how to craft questions that get the best from AI Your career doesn't have to happen TO you. You can build it intentionally. Which certificate speaks to you most? 📌 Want this PDF & the certification links? https://lnkd.in/e5EjDQXZ ♻️ Repost to help your network uplevel their career 🔔 Follow Ashley Couto for more daily career content

𝗧𝗵𝗲 𝗰𝗮𝗿𝗲𝗲𝗿 𝗽𝗮𝘁𝗵 𝘁𝗵𝗲𝘆 𝗽𝗿𝗼𝗺𝗶𝘀𝗲𝗱 𝗱𝗼𝗲𝘀𝗻'𝘁 𝗲𝘅𝗶𝘀𝘁. Here's what replaced it. Remember your first manager's "5-year plan"? Junior Dev → Senior Dev → Team Lead → Manager Clean. Linear. Predictable. That ladder broke around 2020. What Actually Happened: Then: Sarah's 8-year climb Help Desk → Desktop Support → Network Admin → IT Manager Same company. Steady progression. Now: Marcus's 4-year web Help Desk → Cloud → DevOps → Product Owner → Solutions Architect Three companies. Multiple pivots. Who has more market value? Who's recession-proof? The New Reality: 𝗬𝗼𝘂𝗿 𝗰𝗮𝗿𝗲𝗲𝗿 𝗶𝘀𝗻'𝘁 𝗮 𝗹𝗮𝗱𝗱𝗲𝗿. 𝗜𝘁'𝘀 𝗮 𝘄𝗲𝗯. Every lateral move creates skill intersections: • Finance + Tech = FinTech goldmine • Marketing + Data = Growth hacking expert • Sales + Engineering = Technical sales leader • HR + AI = Future of people ops The most valuable pros didn't climb highest. They connected the most dots. The Uncomfortable Truth: You're waiting for that promotion. Someone else is building experience portfolio. Makes them indispensable. They're not climbing. They're weaving. 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗽𝗮𝘆 𝗽𝗿𝗲𝗺𝗶𝘂𝗺 𝗳𝗼𝗿 𝘄𝗲𝗮𝘃𝗲𝗿𝘀. 𝗡𝗼𝘁 𝗰𝗹𝗶𝗺𝗯𝗲𝗿𝘀. 💭 Ladder or web strategy? What needs to change? 🔁 Repost to help other IT professionals  🔔 Follow me, Coach Dave, for more career insights