Software Engineering Career
The checkout bug at 2 AM, the enterprise mainframe that won't die, and the salary math that changes depending on whether you count the RSUs. The real numbers, the leetcode gauntlet, and what engineers say when the standup is over.
How Much Do You Actually Make?
The median is $132,000. But 'software engineer' covers everything from a junior dev at a startup making $70,000 to a staff engineer at Google with $500,000+ total comp. The FAANG/Big Tech salary inflation has distorted the entire market's expectations.
Total comp at tech companies includes base, equity (RSUs), and bonus. A $180K base at Meta might be $350K total comp. Non-tech companies (banks, healthcare, retail) pay 30-50 percent less but offer more stability. Remote work has made high-paying roles accessible outside SF/NYC, but some companies are adjusting salaries by location.
What Do You Actually Do All Day?
The image: writing elegant code in a quiet room. The reality: reading other people's code, sitting in meetings about code you haven't written yet, reviewing PRs, and debugging something that worked yesterday but doesn't today for reasons nobody can explain.
How to Get In
Learn Programming Fundamentals
CS degree (4 years) is the traditional path. Bootcamps (3-6 months), self-study, and community college are all viable alternatives. Python, JavaScript, or Java are common starting languages. Data structures and algorithms matter for interviews.
Build Projects and a Portfolio
Personal projects, open source contributions, or freelance work demonstrate ability. GitHub profile matters. Side projects show initiative.
First Engineering Role
Junior developer, associate engineer, or intern-to-hire. The first role is the hardest to get. After 1-2 years of experience, the market opens significantly.
Specialize (2-5 years)
Frontend, backend, full-stack, mobile, data engineering, ML engineering, DevOps/SRE, security engineering. Your first few years will be generalist; specialization comes with exposure.
Alternative paths: Bootcamps (App Academy, Hack Reactor, Lambda School) have mixed track records but do produce working engineers. Self-taught developers are common and successful, especially in web development and startups. Career changers from math, physics, finance, and other quantitative fields transition well.
Job Outlook
The BLS projects 25 percent growth through 2032, much faster than average. Despite AI concerns and periodic tech layoffs, the long-term demand for software engineers remains strong.
Growing sectors: AI/ML engineering, cloud infrastructure, cybersecurity, healthcare tech, and climate tech are the fastest-growing domains. Engineers who can build AI-powered products are in extreme demand.
Challenges: Basic web development and simple CRUD applications face more competition from AI coding tools and low-code platforms. The bar for entry-level roles is rising as tools get more capable.
Technology shift: AI coding assistants (Copilot, Cursor, Claude) are changing the workflow but not eliminating the role. Engineers who use AI tools are significantly more productive. The role is shifting from 'writing code' to 'directing and reviewing code,' but the underlying engineering judgment remains human.
Honest Pros and Cons
The Good
- Exceptional compensation, especially in tech
- 25% job growth, strong demand
- Remote work is standard
- Creative problem-solving daily
- Clear career ladder (IC and management tracks)
- Skills transfer across industries
The Hard Truth
- Leetcode interview gauntlet is brutal
- On-call rotations and production incidents
- Tech layoffs create anxiety despite strong market
- Ageism concerns after 40
- Imposter syndrome is pervasive
- AI disruption anxiety is real (even if overblown)
Career Paths
Frontend Engineer
User interfaces, React/Vue/Angular, browser performance. Closest to the user.
Backend Engineer
APIs, databases, server infrastructure. The plumbing that makes everything work.
Full-Stack Engineer
Both frontend and backend. Common at startups. Broader but shallower expertise.
ML/AI Engineer
Building and deploying machine learning models. Hottest specialty right now.
DevOps/SRE
Infrastructure, reliability, deployment. Keeping systems running at scale.
Engineering Manager
Leading teams. Less coding, more people management, hiring, and strategy.
Go Deeper
We've talked to working professionals about every angle. Real voices, real numbers, zero sugarcoating.