Ranking the Top 10 High-Paying Tech Jobs in 2026 (Salary + What They Do)

Table of Contents

• Why Top 10 Tech Jobs Feel Like Apartment Hunting
• AI / Machine Learning Engineer
• Cybersecurity Engineer
• Software Engineering Manager
• Cloud Architect
• Data Scientist
• DevOps Engineer
• Technical Product Manager
• Enterprise Architect
• Network Architect
• IT Manager / CTO (Small to Mid-Size Orgs)
• How to Use This Ranking to Choose a Career
• Frequently Asked Questions

AI / Machine Learning Engineer

On paper, AI and machine learning look like the glossy downtown lofts of tech: eye-watering total comp, cutting-edge problems, and every “top paying jobs” list putting them near the top. Typical base salaries land around $140,000-$210,000, with elite roles at top labs and Big Tech hitting $400,000-$600,000+ in total compensation - and some frontier research or staff positions crossing the $1.5M+ mark when you count equity. Salary guides note AI/ML roles seeing pay growth up to 4.4%, compared with a tech-wide average around 1.6%, and job growth estimates sit at roughly 35%+ as every industry scrambles to “add AI.”

The on-paper view (salary, demand, growth)

Across multiple rankings of high-paying tech jobs, AI/ML Engineer shows up in the top tier for both current pay and upside. Analyses like the Alexander Technology Group’s breakdown of AI compensation consistently place experienced ML engineers and applied researchers well into the six-figure base range, with total comp climbing quickly at larger companies and hedge funds. IEEE’s look at 2026 tech salary trends highlights AI and ML as outliers: salaries are still accelerating while much of the market has cooled to that ~1.6% annual bump. That said, the very top packages are rare and fiercely competitive - you’re not just competing with bootcamp grads, but with PhDs, Kaggle champs, and ex-Big Tech engineers.

"AI and machine learning skills are commanding a premium as companies compete for a relatively small pool of specialists who can actually build and ship these systems."
- Technology salary trends report, IEEE-USA InSight

What it feels like to live here (day-to-day and stress)

Day to day, AI/ML Engineers spend most of their time in Python notebooks and code, not on stage talking about “the future.” You’re cleaning messy data, engineering features, choosing and tuning models, and wiring those models into real products. That might mean a recommender system for an e-commerce site, a fraud detection model for a bank, or an LLM-powered chatbot baked into an internal tool. You’ll also own the unglamorous parts: monitoring model drift, debugging training pipelines, managing GPU-heavy infrastructure, and negotiating tradeoffs with product and data teams when the model is “good enough” but not perfect. The work can be intellectually satisfying but also mentally draining - especially under launch deadlines or when experiments fail for a week straight.

Fit check for beginners and career-switchers

This is a steep but not impossible climb. You’re looking at roughly 18-36 months of focused work to go from zero to “hireable in an ML-adjacent role” if you’re starting from scratch, faster if you already code or have a math/stats background. The realistic first stops for most people are roles like Data Analyst, Junior Data Scientist, or Backend Engineer with ML integration work, then specializing further over a few years. You need solid Python and SQL, comfort with statistics, and the patience to iterate on models that fail more than they succeed. If the idea of debugging a training job at 11 p.m. sounds miserable, this may feel more like a noisy downtown loft than a dream apartment.

Practical entry ramp (what to learn first)

A grounded path is to start with production-friendly programming and data skills, then layer on AI. For example, you might use an affordable backend program to get comfortable with Python, databases, and basic DevOps, then add applied AI on top. Nucamp, for instance, offers three relevant tracks that many career-switchers chain together:

Those programs sit in the $2,124-$3,980 range, notably lower than many $10,000+ competitors, and Nucamp reports about 78% employment, 75% graduation, and a 4.5/5 Trustpilot rating across roughly 398 reviews - with one reviewer calling out the mix of “affordability, a structured learning path, and a supportive community of fellow learners.” From there, the portfolio matters as much as the certs: think a recommender system built on public data, a fine-tuned LLM chatbot over a niche corpus, or a small fraud detection model deployed behind an API. Those are the “photos” that help hiring managers picture you living in this particular apartment, not just admiring it from the street.

Cybersecurity Engineer

If AI is the flashy downtown loft, cybersecurity is the sturdy building that never has empty units. On the spreadsheet, experienced Cybersecurity Engineers sit in the $140,000-$225,000 range, with top specialists and security leaders pulling in up to $760,000+ in total compensation at elite firms. Executive roles like CISO often land around $220,000-$260,000+, and there’s a well-documented global talent shortfall of roughly 4 million security professionals. Even when the rest of tech cools off, companies still have to keep attackers out and auditors happy.

Multiple rankings of high-paying IT roles flag security as both lucrative and unusually stable. Overviews like the one on Programs.com’s highest-paying cybersecurity jobs list show security architect, penetration tester, and incident responder roles all clustered well into six figures, with steady growth across finance, healthcare, and government. Research.com’s breakdown of top-paying IT careers reaches the same conclusion: security sits in the top tier for compensation and demand, not just at tech companies but anywhere data and regulation collide.

"Organizations are paying a premium for cybersecurity expertise, particularly for candidates who combine hands-on skills with advanced certifications and an understanding of business risk."
- Pay analysis report, Payscale (via Yahoo Finance)

What it feels like to live here

Cybersecurity Engineers are the people making sure the “building” doesn’t get broken into at 3 a.m. In practice, that means a mix of design work, tooling, and incident response. You’ll design and harden network and system architectures, configure firewalls and intrusion detection, run vulnerability scans, and coordinate fixes with dev and ops teams. When things go wrong, you’re combing through logs, correlating alerts in a SIEM, and helping contain breaches. The job can be calm for weeks and then suddenly very intense when a zero-day drops or an incident kicks off, especially if you’re part of an on-call rotation.

• Design secure network and system layouts (often aligning to frameworks like NIST)
• Implement and maintain tools such as firewalls, EDR, and SIEM platforms
• Run regular vulnerability assessments and prioritize remediation work
• Partner with developers on secure coding and DevSecOps practices

Skills, certs, and why they matter

The technical foundation looks a lot like classic IT plus a security twist: networking (TCP/IP, DNS), operating systems (Linux and Windows internals), cloud basics, and a solid understanding of how attackers actually operate. On top of that, certifications carry real financial weight. According to an analysis summarized by Yahoo Finance, credentials like CISM, CCSP, and CEH can add well over $18,000-$22,000 to average pay, with corresponding jumps in total compensation.

Fit check and realistic entry ramp

For beginners and career-switchers, security is demanding but very doable within 2-4 years if you’re methodical. It tends to reward people who are detail-oriented, curious about how systems break, and okay with occasional adrenaline spikes during incidents. A common path is IT support → Systems or Network Admin → Security Analyst → Security Engineer. To speed that up, many people combine self-study with a focused bootcamp: for example, Nucamp’s Cybersecurity bootcamp runs 15 weeks at about $2,124, covering network security, ethical hacking fundamentals, and incident response basics, and then pair it with Security+ prep. From there, hands-on labs (Hack The Box, TryHackMe), home labs, and small portfolio projects - like hardening a Linux server or documenting a CTF walkthrough - help you prove you’re ready to “move into” the security floor of the building, not just tour it from the lobby.

Software Engineering Manager

The on-paper view (salary and demand)

In the spreadsheet, Software Engineering Manager looks fantastic: salary ranges around $187,500-$287,000, with broader surveys putting the median near $149,000 and top-tier total compensation at large tech companies reaching $900,000+ when you factor in equity and bonuses. Most people who land here have about 5-10 years of experience as Senior or Staff Engineers first. Salary guides like Motion Recruitment’s 2026 tech salary guide consistently show engineering leadership roles clustered near the top of pay bands, especially in markets where competition for senior talent is fierce. Demand stays steady because any engineering org beyond a handful of devs needs someone coordinating people, process, and roadmap.

What the job actually feels like

Day to day, this role is much more about people and outcomes than about writing code. A typical week is packed with 1:1s, sprint planning, roadmap discussions, hiring interviews, cross-team syncs, and the occasional escalation when a project is slipping. You’ll still use your technical background constantly - reviewing designs, asking the right questions about tradeoffs, and making judgment calls on scope - but you’re rarely the one implementing features. Instead, your work looks like:

• Leading a team of 5-15 engineers through planning, execution, and delivery
• Partnering with Product Managers on roadmaps and priorities
• Resolving blockers and cross-team dependencies before they turn into crises
• Handling performance reviews, promotions, and sometimes tough conversations

Tradeoffs: stress, politics, and less code

The pay bump comes with different kinds of stress. You’re accountable for team output, morale, and hiring quality, even when priorities change or dependencies slip. Your calendar can fill with meetings, and you’ll spend more time in documents and dashboards than in an IDE. When things go well, your team gets the credit; when they don’t, you answer for it. For people who love mentoring and strategy, that’s energizing. For others, it feels like giving up the craft. This is more like building management than swinging a hammer - you still live in the building, but your job is keeping everyone else productive and safe.

Fit check for beginners and career-switchers

This is not an entry-level “apartment.” Realistically, you need several years as a solid individual contributor first: shipping production systems, owning projects, and informally leading initiatives. It fits people who enjoy coaching, negotiation, and long-term product thinking as much as they enjoy tech. If you’re a beginner or mid-career switcher, the near-term goal is not “Engineering Manager” but “competent developer who others naturally follow.” You can still bias toward this path early - by mentoring peers, volunteering to run standups, or taking ownership of cross-functional projects - but the title itself usually comes later.

Practical path into engineering management

A realistic route is IC → Tech Lead → Engineering Manager. That starts with becoming a strong developer. Here, structured but affordable programs can help you get that first job without taking on $10,000-$20,000 of bootcamp debt. Nucamp’s Full Stack Web & Mobile bootcamp runs 22 weeks for about $2,604, and the Complete Software Engineering Path spans 11 months at roughly $5,644, covering front end, back end, and practical project work. Once you’re in industry, you gradually take on leadership responsibilities - mentoring juniors, running small projects, then leading a squad - until a formal Engineering Manager role is the obvious next step.

Cloud Architect

On the spreadsheet, Cloud Architect looks a lot like a corner unit with great views: salary ranges around $160,000-$252,000, with average total pay often clearing $200,000 for experienced folks designing large-scale systems. Broader surveys put many Cloud Architects in the $130,000-$187,000 band, especially in major metros, and they routinely show up near the top of lists like WeCP’s ranking of the highest-paying tech jobs in the US. As more companies finish their “first wave” of migration, the premium shifts from just knowing AWS or Azure to being able to design secure, resilient, and cost-efficient architectures that don’t fall over on Black Friday.

Living in this role day to day, you’re basically doing city planning for a company’s infrastructure. You’re evaluating whether workloads belong on AWS, Azure, GCP, or on-prem; sketching out VPCs, subnets, identity and access strategies, and failover plans; and reviewing designs from dev and DevOps teams. You spend a lot of time in diagrams and docs, but you’re still close to the metal: spinning up proof-of-concept environments, reviewing Terraform plans, and digging into performance or cost anomalies. When things break, you’re one of the first calls. When they don’t, most people barely notice - which is kind of the point.

The skill stack blends deep platform knowledge with broad systems thinking. In practice that usually means:

• At least one major cloud at an advanced level (AWS, Azure, or GCP)
• Infrastructure as Code with tools like Terraform or CloudFormation
• Containers and orchestration (Docker, Kubernetes, ECS/EKS/AKS)
• Networking and security: VPC design, IAM, encryption, zero-trust patterns
• Cost optimization and capacity planning for large, spiky workloads

"Cloud expertise has shifted from 'nice to have' to a strategic necessity, and organizations are willing to pay more for professionals who can architect environments that are secure, scalable, and cost-effective."
- 2026 Compensation Trends and Salary Guide, Blue Signal Search

For beginners and career-switchers, this is more of a second- or third-stop apartment than a starter studio. You’re usually looking at several years as a Cloud or DevOps Engineer before you’re trusted with full-architecture decisions. The good news is that the entry ramp into those feeder roles is clearer now: start by getting comfortable with Linux, Python, and basic cloud services, then layer on CI/CD and Infrastructure as Code. An affordable way to do that is something like Nucamp’s Back End, SQL & DevOps with Python bootcamp, a 16-week program around $2,124 that covers Python, SQL, APIs, and deployment fundamentals. From there, you chase one associate-level cloud cert, build a few real deployments (e.g., a containerized app on Kubernetes, a serverless API), and gradually take on more design responsibilities until “Cloud Architect” is just the title that matches what you’re already doing.

Data Scientist

For a lot of people coming from business, finance, or science, “Data Scientist” is the first cell that lights up on those top 10 spreadsheets. The numbers look great: typical salaries around $120,000-$211,000 for mid-to-senior roles, with top-tier positions at places like Meta or Netflix crossing $300,000 in total compensation. Data jobs also show up near the top of lists like UT Dallas’s overview of highest-paying tech careers, and they cut across nearly every sector: healthcare, retail, SaaS, finance, government. While broader tech job growth hovers around 15% versus roughly 3% for the overall market, data-focused roles consistently rank among the most in-demand inside that slice.

The on-paper view (salary and demand)

On paper, Data Scientist looks like a sweet spot: high six-figure potential without needing to be a world-class algorithm researcher. Surveys that group data roles together, like the breakdowns on Salary Transparent Street’s high-paying tech jobs hub, show strong median pay and solid upward mobility into Staff, Principal, or analytics leadership tracks. Demand is diversified, too: even companies that are conservative about AI experiments still need forecasting, churn models, and solid reporting. That mix of good pay and broad industry appeal is why this role keeps showing up on “best job” lists year after year.

What it feels like to live here

Day to day, most Data Scientists are closer to “very technical analyst” than “lone genius building magic black boxes.” You’ll spend a surprising amount of time cleaning and joining data, exploring patterns, and building understandable models: regressions, classification, time-series, maybe some lighter-weight machine learning. A typical week might include designing an A/B test, writing SQL to pull data into a notebook, building a model in Python, and then explaining the results to stakeholders who don’t speak stats. You’re often the bridge between raw data and business decisions: should we launch this feature, change this pricing, or double down on this marketing channel? When it’s good, it feels like solving puzzles that actually matter; when it’s bad, it’s fighting messy data and last-minute “can you just pull a quick number?” requests.

Skills that matter and how roles compare

The core toolkit is well known: SQL for querying, Python or R for analysis and modeling, and libraries like pandas, NumPy, and scikit-learn. Add in basic stats (hypothesis testing, regression, experiment design) and a BI tool or two (Tableau, Power BI, Looker), and you’ve covered what many companies expect. Where things diverge is how deep you go into math and ML versus business context. Roughly, the “data neighborhood” breaks down like this:

Fit check and realistic entry ramp

This “apartment” fits people who like numbers and patterns but also enjoy explaining things in plain language. You don’t have to love hardcore math, but you do need enough comfort with statistics that terms like “p-value” and “confidence interval” don’t make you flinch. For beginners and career-switchers, an honest timeline from zero is about 18-36 months to reach a solid entry role, faster if you already work with data in Excel or BI tools. The realistic first job for most switchers is Data Analyst or BI Analyst, then moving into a Data Scientist title as your modeling chops grow. A pragmatic path is to get fluent in SQL and Python first (for example, through a backend-focused program that forces you to work with real databases), then layer on stats, portfolio projects like churn prediction or sales forecasting, and finally some lighter ML. Think of it as moving into the data neighborhood at street level, then taking the elevator up a few floors once you’ve proved you can actually live there.

DevOps Engineer

DevOps Engineer is one of those roles that doesn’t always get the flashiest title, but keeps showing up near the top of any serious tech-career spreadsheet. Salary-wise, you’re typically looking at around $113,000-$175,000, with median total pay near $145,750 for people who can reliably ship and run software in production. On the demand side, DevOps keeps showing up in “most in demand” lists because every company that writes software eventually hits the same wall: they need someone who can automate deployments, keep systems up, and tame an ever-growing pile of services.

The on-paper view (salary, demand, remote)

Across multiple salary and market reports, DevOps is treated less like a fad and more like core infrastructure. Guides that track high-paying roles, like the in-demand tech jobs rundown from Metana’s 2026 tech jobs analysis, consistently list DevOps and related titles (SRE, Platform Engineer) as both well-compensated and hard to hire for. The pay bands above are based on ranges reported in major US salary guides, with the upper end pushed higher in big markets and at companies running large-scale, cloud-heavy systems. On top of that, DevOps is one of the more remote-friendly specialties: as long as you can access the cloud console and respond to alerts, you don’t have to be sitting in the data center.

What it feels like to live here

Living in a DevOps role day to day means you’re the person making sure code doesn’t just work on a laptop, but in production at 2 p.m. on a Tuesday and 2 a.m. on a Sunday. You spend your time wiring up CI/CD pipelines, containerizing services, managing Kubernetes clusters or other orchestrators, and setting up monitoring and alerting so you know when something goes sideways. When things are calm, you’re automating away manual work and helping developers ship faster; when things are on fire, you’re triaging incidents, rolling back bad releases, and figuring out how to make sure it never happens the same way twice.

• Build and maintain CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.)
• Containerize applications and manage clusters (Docker, Kubernetes, ECS/EKS/AKS)
• Automate infrastructure with tools like Terraform or CloudFormation
• Set up and tune observability: logs, metrics, alerts, dashboards

How DevOps compares to similar roles

On the org chart, DevOps often sits next to Site Reliability Engineers (SREs) and Platform Engineers. The titles can blur, but the focus is slightly different in each “apartment” of this neighborhood:

Fit check and realistic entry ramp

This path suits people who like building tools for other engineers, enjoy debugging weird infrastructure issues, and don’t mind occasional adrenaline during outages. If you want to break in as a beginner or career-switcher, the most realistic plan is to first get comfortable with one language (often Python), Linux basics, and some web/backend fundamentals, then grow into cloud and automation. A practical way to stack those skills is a focused backend program that includes DevOps concepts: for example, Nucamp’s Back End, SQL & DevOps with Python bootcamp runs 16 weeks at about $2,124, covering Python, SQL, APIs, and deployment. From there, you can build a few concrete projects - a containerized web service with a simple CI/CD pipeline, deployed to a cloud provider with monitoring attached - which show employers you’re not just listing “DevOps” on your resume, you’ve actually lived in the neighborhood long enough to know where the leaky pipes are.

Technical Product Manager

The on-paper view (salary and demand)

Scroll down a typical high-paying tech jobs list and Technical Product Manager is often the first role that looks half technical, half business. On paper, the numbers are strong: salary ranges around $125,000-$175,000, with a projected 2026 median of about $175,296, and senior/principal TPMs at larger companies often clearing $250,000-$300,000+ in total compensation once bonuses and equity land. In rankings like ZipRecruiter’s highest-paying technology jobs overview, product and technical product roles consistently sit near the upper middle of the pack - below executive and niche AI titles, but comfortably above most generalist IC roles. Guides focused on employer demand, such as Snaphunt’s look at top tech jobs and skills, also flag product management (especially with technical depth) as a key hiring priority because it directly affects whether engineering effort turns into revenue.

What it feels like to live here

Day to day, a TPM’s job is less about writing code and more about orchestrating people, problems, and tradeoffs. You’re defining and refining product requirements, translating fuzzy stakeholder requests into clear specs, and working with engineers to break work into shippable chunks. A typical week can include user interviews, backlog grooming, writing tickets, checking analytics, and negotiating priorities when there’s more work than time. You need enough technical fluency to understand system constraints and API interactions, but success is measured in outcomes: features shipped, customer problems solved, and whether the metrics you own (adoption, retention, revenue for your area) move in the right direction. It can be energizing if you like context-switching and decision-making; draining if you prefer long, quiet stretches of focused build time.

How TPM compares to PM and Project Manager

The titles around this “apartment” can be confusing. A lot of people move between Product Manager, Technical Product Manager, and Project Manager, but the emphasis and expectations are different in each:

Fit check and realistic entry ramp

TPM fits people who enjoy systems thinking and tradeoffs: you like understanding how things work under the hood, but you’re more excited about choosing the right problems to solve than about personally implementing every solution. It’s not usually a straight-from-zero starter role; most TPMs arrive via software engineering, data/analytics, or “PM-adjacent” work like business analysis or project management. For beginners and career-switchers, a realistic path is 2-4 years: first get close to the product (as an analyst, associate PM, or ops specialist), then build technical fluency through hands-on coding, SQL, and basic web concepts. Shorter programs - like Nucamp’s Web Development Fundamentals (a 4-week intro at around $458) or a backend/SQL-focused bootcamp - can give you just enough engineering context to talk credibly with dev teams, read simple code and data schemas, and use analytics tools yourself. From there, you target Associate PM, Product Analyst, or Product Operations roles as your “first apartment” in the building, then move into a full TPM title once you’ve proven you can own a roadmap and work comfortably with technical constraints.

Enterprise Architect

Enterprise Architect is less the flashy high-rise and more the city planner’s office: fewer units available, hard to get into, but very well compensated once you’re there. On paper, salary ranges sit around $170,000-$199,000, with senior Enterprise Architects in large organizations often reaching roughly $220,000-$250,000 in total compensation. In rankings of top-paid IT roles, this title regularly shows up near the top because it owns the big picture of how systems, data, and platforms fit together across an entire company.

The on-paper view (pay and scope)

Enterprise Architect is explicitly framed as a late-career, high-impact role in analyses like the highest-paid IT salaries breakdown from ITCompare’s 2026 IT pay report. It’s not just the raw salary that pushes it up the charts; it’s the scope. You’re responsible for aligning technology strategy with business objectives, evaluating major platforms (ERP, CRM, data), and defining long-term architectural roadmaps. There are fewer openings than for, say, cloud engineers or data scientists, but when companies do hire for this, they’re looking for someone who can influence budgets measured in millions.

What it feels like to live here

Day to day, Enterprise Architects spend a lot of time in diagrams, documents, and meetings with senior stakeholders. You’re mapping how dozens (or hundreds) of systems talk to each other, where data flows and piles up, and how to move from today’s mess to a more coherent “target state” over several years. That might involve standardizing integration patterns, choosing a strategic vendor, or setting guardrails for how teams adopt new tools. You’re less hands-on with code and more involved in decisions like “Should we move this business line to a new platform?” or “How do we modernize our data stack without breaking everything?” The wins are slower and more strategic; the flip side is more politics and a lot of responsibility when your blueprint turns into expensive implementation work.

"Leaders are facing a more competitive, more specialized tech job market, and long-term architecture and planning roles are becoming critical to staying ahead."
- 2026 IT Hiring Trends report, Addison Group

Fit check and realistic path into the role

This is almost never a first or even second job; it’s a destination apartment you move into after years in the neighborhood. Most Enterprise Architects have spent a decade or more rotating through roles like Senior Software Engineer, Cloud Architect, Data or Integration Architect, or IT Manager. The pattern is depth first, then breadth: get very good at one domain, then intentionally pick projects that force you to work across systems and teams. The intermediate titles along the way often look like Solution Architect or Domain Architect, where you own architecture for a product line or platform before stepping up to the whole enterprise.

If you’re a beginner or early career-switcher, it’s better to treat Enterprise Architect as a long-term possibility rather than something you aim for in three years. The practical move is to pick a solid starting lane - software engineering, cloud/DevOps, data, or security - then gradually chase cross-functional problems and architecture work as you gain seniority. Think of it as learning to design one building really well before anyone lets you plan the entire city.

Network Architect

Network Architect is very much the “roads and bridges” job in tech: not flashy, but everything stops working if you get it wrong. On paper, experienced Network Architects earn roughly $140,000-$195,000, with senior specialists in telecom, large data centers, or global enterprises going higher when you add overtime or on-call pay. In rankings of top-paying IT roles like the breakdown on Research.com’s highest-paying tech jobs, network-focused architecture consistently shows up in the upper tier, especially for organizations that still run significant on-prem or hybrid infrastructure.

The on-paper view (pay and stability)

Compared with some newer titles, Network Architect looks almost old-school, but salary guides still treat it as a core, well-compensated specialty. You’re designing and overseeing critical infrastructure that directly impacts uptime across offices, data centers, and cloud connections. That makes the role especially entrenched in enterprises, government, and telecom. While growth isn’t as explosive as AI or cloud-native roles, the combination of solid six-figure pay, clear seniority path, and ongoing need for low-latency, secure connectivity keeps this “apartment” occupied even when other parts of the market get soft.

What it feels like to live here

Day to day, Network Architects are crafting and maintaining the blueprints for how data physically moves through an organization. You’re designing LANs, WANs, VPNs, and SD-WAN topologies; choosing routing protocols (BGP, OSPF, MPLS); and planning redundancy so a single fiber cut doesn’t take down half the company. You’ll also work closely with security teams on segmentation, firewalls, and zero-trust approaches, plus cloud teams on VPC/VNet design and hybrid connectivity. When everything’s humming, you might be fine-tuning QoS policies or planning a migration; when something breaks, you’re in the middle of multi-team incident calls tracing packets and logs until you find the bottleneck.

• Design campus and data center networks, including switch and router layouts
• Plan IP addressing, routing policies, and failover strategies
• Integrate on-prem networks with cloud environments via VPN or direct links
• Collaborate with security on firewalls, IDS/IPS, NAC, and network segmentation

How it compares to related roles

The network “neighborhood” spans a few titles, each with different scope and pay. Roughly, it breaks down like this:

Fit check and realistic entry ramp

This “apartment” fits people who like low-level tech, command-line tools, and thinking in diagrams. The work is structured and logical, with deep rabbit holes around protocols and vendor quirks. It’s not usually an entry-level job; a common path is Help Desk → Network Technician → Network Engineer → Network Architect over 5-10 years, depending on how quickly you take on design responsibilities. For beginners and career-switchers, the realistic first step is to learn networking fundamentals (CompTIA Network+ level), get hands-on with gear or virtual labs, and pursue certifications like Cisco CCNA as you move into junior network roles. From there, advancing to CCNP and taking ownership of segments of the network (a site, a region, or a set of data center links) is what gradually moves you from “keeping the lights on” to actually designing where the roads go.

IT Manager / CTO (Small to Mid-Size Orgs)

IT Manager and small/mid-size CTO roles are the “building owner” side of tech: you’re not just living in one apartment, you’re responsible for the whole property. On paper, compensation is strong. IT Manager / Director roles often land in the $171,000-$260,000 range, while CTOs at startups and smaller companies commonly sit around $150,000-$250,000 in salary plus equity. Analyses of executive tech pay, like the projections from Business Insider’s breakdown of 2026 tech jobs, consistently show technology leadership clustered near the very top of pay bands, especially where leaders own both budgets and strategy.

The on-paper view (pay, scope, expectations)

Unlike many specialist roles, these titles are explicitly about breadth. An IT Manager in a mid-size company might oversee all internal systems, endpoints, and vendors, while a CTO in a product-focused startup is shaping engineering direction, hiring, and long-term roadmap. Guides that track the IT job market, such as Campus.edu’s look at IT job and salary trends, note that leadership roles are among the least likely to be cut in downturns, but they’re also among the hardest to break into because they typically require a long, documented track record. On the spreadsheet, the tradeoff is simple: high pay, low volume of openings, and very high expectations around accountability.

What it feels like to live here

Day to day, these jobs are more budgets, people, and vendors than code. You’re sitting in meetings with finance and operations, negotiating SaaS contracts, deciding between “build vs. buy” for major systems, and handling escalations when something critical goes down. A typical week can include planning next year’s infrastructure budget, reviewing security and compliance posture, running staff meetings, and making hiring or performance decisions. In a small startup, a CTO might still jump into code reviews or even ship features; in a more established org, hands-on work is rare. The stress profile is different from IC roles: fewer 2 a.m. debugging sessions, more slow-burn responsibility for whether the entire tech stack and team are moving in the right direction.

• Own technology roadmaps and alignment with business goals
• Manage IT or engineering teams, including hiring and performance
• Set standards for security, reliability, and vendor selection
• Report up to CEOs, COOs, or boards on risk, spend, and strategy

IT Manager vs. CTO in smaller organizations

At small to mid-size organizations, the line between IT Manager and CTO can blur; sometimes one person effectively does both. The rough split usually looks like this:

Fit check and realistic entry ramp

These roles fit people who like owning outcomes more than individual tasks: you’re comfortable being ultimately responsible for outages, hiring misses, and big bets that don’t land. They are not realistic first jobs; you’re usually looking at well over a decade in the field, moving through roles like Senior Engineer, Team Lead, Engineering Manager, and Director of IT or Engineering. For beginners and career-switchers, the practical move is to start as a strong individual contributor, then deliberately pick up management and budget responsibilities. That might mean leading a small dev team, running vendor evaluations, or owning a department’s tooling budget. Structured, affordable programs can help you secure that first engineering role without taking on heavy debt: Nucamp’s Complete Software Engineering Path, for example, spans 11 months at about $5,644, covering front end, back end, and practical projects that get you into the building as a developer. From there, the path to IT Manager or CTO looks less like a straight promotion ladder and more like a series of increasingly broad roles where you prove, step by step, that you can be trusted with more of the “building.”

How to Use This Ranking to Choose a Career

At this point you’ve seen the rankings, the salaries, the “square footage” for each role. The risk now is treating the table like a sorting function instead of what it really is: a short list of places worth touring. You’re not trying to win some abstract “best job” game; you’re trying to find a role that pays your bills, fits your brain, and doesn’t make you dread Monday morning.

Step 1: Start with your non-negotiables, not the rankings

Before you fall in love with a title, get clear on what you won’t trade away. That might be remote flexibility, predictable hours, or the chance to work on consumer products instead of internal tools. Market overviews like Hakia’s tech career analysis keep repeating the same theme: people who align their next move with how they actually want to work (location, pace, learning curve) tend to stick around long enough to see the comp upside. If you ignore that and chase whatever sits at #1, you can absolutely end up in a gorgeous “penthouse” that feels wrong within a year.

• Write down the hours, stress level, and collaboration style you’re okay with.
• Decide how much you care about coding vs. managing vs. analysis vs. customer work.
• Be honest about your timeline: do you need a job in 6-12 months, or can you invest 2-4 years ramping into something more specialized?

Step 2: Tour the role, not just the title

Once you’ve got your must-haves, treat each role like an apartment you’re actually going to visit. That means reading day-to-day responsibilities, watching “day in the life” videos, and even scanning a few real job postings to see what employers actually expect. Resources like Michael Page’s tech job trend reports can give you a sense of which skills are consistently requested across roles, and which are just buzzwords. The goal isn’t to memorize every bullet, it’s to answer a simpler question: can you picture yourself doing this work most days and not hating it?

• Look for 3-5 real job descriptions for the same title in different companies.
• Pay attention to what’s repeated: tools, tasks, soft skills, years of experience.
• Note any “hidden issues in the building” like constant on-call, heavy travel, or vague expectations.

"The most successful moves aren’t just about chasing higher pay; they come from matching your strengths to roles where employers are struggling to hire and promote from within."
- Tech career trends report, Michael Page

Step 3: Pick an entry ramp you can actually commit to

Finally, work backwards from the role to the first realistic job you could land in 12-24 months, given your current skills and life constraints. For some paths that’s a junior developer or analyst role; for others, it might be IT support, QA, or a hybrid operations job that gets you close to the systems you eventually want to own. From there, decide how you’ll close the gap: self-study, an affordable bootcamp, internal training, or some mix. The important part isn’t whether your route is “perfect”; it’s whether you’ve chosen a ramp that fits your situation well enough that you’ll stay on it when things get hard. The list you just read is a map of neighborhoods, not a verdict. Your job now is to pick one or two that seem promising, start touring seriously, and then sign a “lease” on a path that gives you both enough square footage and enough sunlight to actually live there.

Frequently Asked Questions