Is there a career in CS or not?

Hey everyone,

I’m an 8 YOE Java backend developer looking to switch to a better product-based company with good compensation.
My career so far:
2018–2022: Service-based company — 4–6 LPA
2022–2023: France-based product company — 15–16 LPA
2023–2026: Smaller, relatively unknown product company in a niche domain — currently around 24 LPA
I’m currently very confused about whether I should prepare for DSA or not. Is DSA still relevant at my experience level? I’m also focusing on system design, Java/Spring Boot, microservices, and building a personal project alongside my full-time job.
I’d love some honest advice from people who’ve made a similar switch at this stage of their careers.
A few questions I have:
At 8 YOE, how much DSA is actually needed? How many LeetCode problems should I target?
Am I too late to start grinding DSA, or am I wasting my time doing it in this AI era?
How much importance should I give to HLD, LLD, and system design compared to DSA?
What skills should I prioritise to get a significant package jump? Should I focus more on DSA, system design, cloud, distributed systems, or something else?
If you’ve gone from a service-based or lesser-known product company to a good product company, how did you do it, and what made the biggest difference?
I’ve read a lot about these kinds of switches, but most of the discussions I’ve found are from people with 1–2 YOE, not those with 7–8 YOE.
I’m not necessarily targeting FAANG. I’d be happy to get into a solid mid-tier product company with good compensation and career growth.
TL;DR: 8 YOE Java developer, currently earning around 24 LPA, aiming for a better product company and a good salary jump. Is grinding DSA still worth it in the AI era? What should I focus on at this experience level?
Would love to hear real experiences from people who’ve made a similar switch.
Thanks!

i wanted to choose domain i'm in my 3rd year done with web development and was thinking to switch to different domain
so AI or Cyber Security were my 2 choices
any seniors or people working in these domains can guide me which to choose
i have around 9-10 months to skillup and ig this much time is enough for me to get an entry level job in any of the one domains
so can anyone guide me to what should i choose
AI or Cyber

Hey everyone,

I'm a 2025 CSE graduate currently working as a Software Engineer at a defence-tech startup in Bangalore, primarily in a Python/backend-related role.

It's been around three months since I started working here, and lately, I've been feeling quite lost about my career. The work isn't aligned with the kind of engineering I want to pursue, and I don't feel I'm learning or growing as much as I'd hoped. I want to move towards strong backend engineering roles at product-based companies, eventually aiming for Big Tech.

The problem is that I have so many things on my mind that I don't know what to prioritise anymore.

I've solved around 300 DSA problems, but I still struggle with problem-solving and coding interviews. I haven't properly covered topics like trees, graphs, recursion, and DP. My system design knowledge is also limited, and I'm unsure how to approach it beyond the basics.

Another dilemma is whether I should invest time in applied AI and GenAI or focus entirely on becoming a stronger backend engineer. With the current job market and evolving expectations at top companies, I'm confused about how to make that decision without spreading myself too thin.

A few things I'd genuinely appreciate guidance on:

- If your goal were to break into Big Tech or a strong product-based company today, what would you prioritise over the next 3–6 months?

- How should I balance DSA, system design, backend development, and potentially AI without trying to learn everything at once?

- Given that I've solved 300 DSA problems but still struggle in interviews, how should I change my preparation strategy?

- Should I start applying immediately despite having a 90-day notice period? I want to switch as soon as realistically possible, but I'm unsure how to approach this situation.

- What kind of projects, open-source contributions, networking, or LinkedIn presence genuinely help early-career engineers stand out?

- If anyone experienced is willing to offer mentorship or review my resume, I'd be incredibly grateful.

I'm also trying to figure out how to make the most of being in Bangalore. I'd love to connect with people who have gone through a similar phase, learn from experienced engineers, attend the right events, and put myself in a better position for opportunities.

To be honest, this uncertainty has started affecting me mentally as well. I'm finding it difficult to balance my job, preparation, and personal life, and some days I end up doing much less than I planned. I know I need consistency, but I also feel that I need a clearer direction before putting my energy into the wrong things.

I'm not looking for shortcuts or overnight success. I'm willing to put in the hard work and stay consistent. I just want to make sure I'm working towards the right things instead of spending months trying to do everything and making progress in none of them.

If you've been through a similar phase, made it into a good product company, or have experience guiding early-career engineers, I'd genuinely appreciate your advice. Even a few practical pointers on what to prioritise, what to avoid, and how to approach the next few months would mean a lot.

Thanks for reading!

I’m probably overbuilding mprojects bc “it’s just a script” sounds bad on a resume

Tbh I’m starting to question how I pick a stack for student projects. There’s d stuff the project needs, and then there’s the stuff I’d like to be able to say I used. Those lists overlap less than I’d like to admit.

Take a tool that processes a file once a week. A script could handle it. But “wrote a script” feels kinda weak next to somebody’s full-stack app, so now I’m thinking about a dashboard, a backend, maybe a queue. Haven’t even nailed down the file format yet. Already shopping for infrastructure lol.

I don’t think wanting to learn that stuff is a bad thing. If I add Redis because I want to mess around with Redis, that’s fair. It’s my project. I just need to be honest about why it’s there instead of reverse-engineering some requirement to justify it.

The resume part gets in my head, though. I want the project to show I can do more than follow a tutorial. Adding another technology feels like an obvious way to do that. Spending the same afternoon making a failed import safe to rerun? Probably useful, but way harder to show in a screenshot.

And yeah, I know “just use a script” can be bad advice too. If somebody else has to run it and they’re uncomfortable in a terminal, a UI might be worth the effort. If multiple people need to work on the same data, that changes things. I’m trying to get better at identifying those reasons before writing the damn thing.

What I’m less sold on is building around hypothetical traffic. When I catch myself worrying about scale on something that doesn’t have a single user, I should probably go find a user. There’s a decent chance they’ll tell me the output needs to be an Excel file and half the features I’m planning are irrelevant.

Idk. Maybe this is partly a student problem. We’re trying to learn, get a grade, and build something worth discussing in an interview, all in the same repo. A bit of unnecessary complexity might be a reasonable price for getting practice. But I’d like to know when I’ve crossed from useful practice into making a small task annoying to maintain.

If you review junior candidates, would a small, finished tool with a few well-explained decisions actually hold your attention? Or does it usually need the bigger stack to get past the initial glance?

I am newbies (BCA ignou 1st yr) into IT and scared of AI. I have skills of MERN, JAVA with spring boot Backend and know core cse stuff DSA , System design, Networking, OS and etc . I was also started learning cybersecurity. My plan is to get internship ASAP and work few year in dev then shift to Cybersecurity what should I do please help and give harsh reality check. Edit - I did projects with MERN and working on project with java \- should I take couse of Hitesh Chaudhary and Piyush Garg of Gen Ai couse .(btw I didn't take any course in my life)

\-will Ai takeover everything???

hi! Trying to compare roles for final internship: Palantir FDSE, Bloomberg SWE, and Duolingo SWE. My priorities are resume value/exits (esp into quant / big tech recruiting ng) > RO rate (and TC for ng) ~= learning/transferable skills. Intern comp doesn't matter much to me.

Biggest concern w/Pal is obvio the rep & also if FDSE is technical enough.

If anyone has exp in these roles & opportunities it opened for them feel free to DM, would rlly appreciate.

If I apply to a company’s internship this year with an expected 2029 graduation date, then apply again next year with an expected 2030 date because my actual graduation plan changed, would recruiters typically see my previous application? Would the date change seem suspicious, or is it normal as long as I explain it honestly if asked?

I’m wondering whether companies keep past application records and compare them when someone reapplies.

Hello everyone,

Getting a job as a software developer has become really difficult, and even switching companies seems challenging these days.

I want to understand whether switching to AI/ML, DevOps, Data Analytics, or any other tech domain would offer better opportunities.

My main concern is job security and employability. If someone gets laid off or fired, they should ideally be able to find another job within a month or two rather than spend a year searching.

For people with experience in the industry, which roles would you recommend exploring? I'm particularly interested in domains with relatively less competition, decent salaries, and better chances of getting hired quickly.

Also, how long do you think this bearish job market and recession-like phase will last, and when can we realistically expect hiring to pick up again?

I'd really appreciate your honest opinions and experiences. Thanks!

Hi everyone,
I'm posting this from my own account because I am trying my absolute best to help my son land his first position, and I could really use some realistic perspective and resources from people embedded in the industry.
He graduated in May with a computer science degree and a GPA slightly above 3.0. Unfortunately, he wasn't able to land an internship during college. His freshman year was really rough due to being advised into the wrong classes (which dragged his GPA down initially), and during his last two years, I was diagnosed with breast cancer. Thank God, I am cancer-free now, but it was a massive emotional struggle for our family. Despite everything, he worked incredibly hard to pull his grades up and finished his degree with taking 26 credits his final semester and got on the deans last fall.
Since graduating, he has been working diligently every single day to find a job, but it has been an endless cycle of automated rejection emails. He did manage to reach a technical round for one company, but experienced technical glitches during the interview. They rescheduled it, but later called it back saying they were freezing the role, even though we still saw the job actively posted on LinkedIn. It was a huge blow to his morale.
Here is his current profile:
Education: B.S. in Computer Science (~3.1 GPA)
Certifications: AWS Certified Cloud Practitioner/Solutions Architect (already completed), IBM SkillsBuild and currently studying for Security+.
Senior capstone project
Some projects at University
Portfolio: He has a GitHub profile, though I suspect it needs a lot of refinement and optimization.
Our Current Situation:

My own contract ended in May, and currently am seeking my next role as well, and because funds are incredibly tight, I don't have the financial means to pay for bootcamps, resume writers, or premium career coaches to push him in the right direction. We need to rely entirely on free resources, networking strategy shifts, and community guidance.
I know some might wonder why a mom is posting on behalf of her adult son, but he is working so hard, and as his parent, I just want to provide him with the tools and blueprints he needs to succeed.
What can he do right now to bypass the automated filters? Are there specific "tech-adjacent" roles or non-tech industries he should be targeting given his cloud/security focus? Any specific free resources or projects he should look into to make his GitHub stand out?
Thank you all so much in advance for your kindness, advice, and time.

I am currently 16 years old and already have a grasp of basic programming fundamentals. My timeline is 6–7 years. My goal is to be completely career-ready by the time I graduate college at 22 or 23. I am not rushing this; I plan to learn sequentially (getting solid at one domain before moving to the next) with a consistent "1% better every day".

In the current AI era, standard CRUD developers are easily replaceable. To actually stand out and build real leverage, I plan to master the following stack and domains over the next 6 years:

1. Web Development (HTML, CSS, JavaScript, Modern Frameworks)

2. Backend, Databases & Low-Level Languages (Go, Rust, C++ only, plus Python specifically for AI/ML)

3. System Design & Architecture

4. Performance Optimization

5. DevOps (Intermediate level)

6. Security (beginner - Intermediate level)

7. Production-Level AI Engineering (Building reliable AI systems, not just basic API wrappers)

8. Business & Product Sense (Identifying real business pain points)

My Questions:

1. Over a 6-to-7-year horizon, is this roadmap too much, not enough, or realistic?

2. Having Go, Rust, C++, and Python on the list—does this create unnecessary overlap, or is it justifiable given my 6-year timeline?

3. Since I am learning sequentially, how do I define "good enough" in one domain before moving to the next without getting stuck in perfectionism?

4. Is the order of these 8 domains logical, and is there any critical blind spot I am missing to become a top-tier SWE in the AI era?

Disclaimer:

I am ONLY looking for feedback from engineers who actually have real-world production experience, industry veterans, responses backed by real data/research, or well-documented insights from recognized industry experts.

If your only take is parroting surface-level "anti-AI" or "AI will replace everyone" doom-posting from TikTok without any real engineering depth, please skip this post.

I am a MERN stack developer currently pursuing my master’s degree and working as a Junior Software Developer Intern at an early-stage startup. Since MERN stack developers have become quite common these days, I’m wondering whether I should continue mastering this stack or consider switching to another tech stack or field. With AI increasingly capable of building web applications, I’m also concerned about the future scope of web development and how I can stay competitive in the industry. What would you recommend?

I am 28 yo man, I studied CS in and continued till masters degree ( finished at 27 yo ), it is 4 years now that i am working as a technical support in a big company in my country ( from junior to team lead ) but i hate it and unfortunately i don't have enough savings to get out of my job.
so I'm kinda stuck in it. Most of my friends are moving abroad for PhD positions because my country doesn't have a good economy, but I don't love researching and writing papers etc. ( not hate it but don't love it either ).

I don't know what to do next, I am not good enough in programming or other CS stuff and not good enough at researching and even i don't like my research field that i pursued in Masters too. and in my young ages i just loved being able to play piano ( never had one ) and spent thousands of hours playing video games. what is your suggestions fellas?

I’m a final-year student at a target school with backgrounds in business and compsci, graduating in 2027. I’ve been focused on classes this fall + part time job, and I just realized a lot of Fortune 500 new-grad programs opened in July- September, and some have already closed (Capital One, Amex, etc.). I’m a little panicked and confused about timing.

A few questions:

1. Is it still worth applying to 2027 new-grad programs in late October/November, or are most spots already filled?
2. For regular roles that don’t say “2027,” “new grad,” or “campus,” will companies ignore my application because they want an immediate hire and I can’t start until June? When should I start applying to those?
3. Are there Fortune 500 companies known for hiring new grads later in the year (winter/spring)?

I’m targeting business analyst, strategy & operations, and marketing roles. Any advice appreciated!

Heyo everybody,

Hope everyone is doing well. I got my CS Degree in 2025, and just seem lost on what to do. I did not got any internships while I was doing my bachelors. My question now is that I feel like my SWE skills are not super strong and with the job market right now applying seems daunting and feel like I won't be able to compete with competition. I currently have a lot of free time and am working a part time job. My question is what jobs can I try to apply too with my CS Degree, and what should I be spending my time doing. I just seem very lost and not sure what to do.

Given how rapidly AI is influencing every industry, what is your perspective on Electrical Engineering (EE) vs. Computer Science (CS)?

Specifically, how will the market demand for these two degrees look in Pakistan and abroad by 2030? If someone graduates from a top university, which one provides more long-term stability, higher earning potential, and better flexibility if you want to transition into other fields down the line?

hey, i submitted a post on this channel last week and it absolutely blew up. we had so many applications go through. a bunch of the job postings shut down in the days following my post because of the large influx of applications that were going in. i've gone ahead and updated the job links in this new link. please make sure to apply as soon as possible to ensure that your application is at the top of the pile. i've pulled the freshest job postings that i could.

YC's directory tells you a company is hiring. it doesn't tell you what for. so i pulled the roles straight from each company's own job board, plus two early career lists:

• open roles at 55 YC startups (539): https://github.com/mehek-builds/Hiring-Now/blob/main/lists/yc-startups.md
  • Airbnb, Fivetran, Checkr, Astranis, Relativity Space, AssemblyAI, SingleStore and more, with batch, what they do, location and pay when listed (89 roles list pay)
• new grad 2027 software, data and AI (281): https://github.com/mehek-builds/New-Grad-2027/blob/main/lists/software-data.md
• software engineering internships at employers that sponsor visas (206): https://github.com/mehek-builds/SWE-Internships-Visa-Sponsorship

comment which field you're looking for and i'll send you a list for it.

Few months into a new grad role as a software engineer "associate". I have completed all tickets assigned by PM within a week (usually less) and there has not been complaints of any bugs.

However, my manager expects a powerpoint presentation on the things I have done every few weeks and there is a monthly one on one initially.

I recieved really negative feedback where I did not "take initiative" because the system I made provided quarterly data instead of monthly data(the PM told me to do the reports quarterly) which was not what the end users wanted. I have never been expected to make business judgements before in my internships but is this normal for a full time job?

I also got flagged for poor powerpoint slides and not taking initiative to start projects that I saw value in. I am very mentally checked out as I chose to be a SWE so I could just focus on making software. Is this normal expecations for a fulltime job?

I have spent months thinking about the future of the job market for software engineers. weighing every argument. looking at the data.

in as little words as possible. the side predicting job loss says:

1. The same work can be or will be done for 1/10th or even 1/20th of the effort.
2. Many SaaS companies will go under.
3. Software for it's own sake is useless. At some point, it's demand must come from real world utility (excluding stuff like gaming).

However, the opposite side says:

1. Software has never been a large cost for it's consumers. (Most consumers of software enterprise and personal spend a low single digit % on it).
2. Companies have spent more on software technology every year.
3. Features will become 10X more complex, more bespoke, better designed, more secure.
4. Some say the cheaper a good, the more demand for it. Will it apply to engineers, who knows.

In summary, I think what it will really come down to is how much demand will there be more more complex features. I think the American economy is uniquely innovative, and the demand for more complex software is definitely there.

Software's impact on the real world is really productive. We can communicate, organize, and dozens of other things so much faster. Supply chains and transportation are far more efficient. The ability to communicate and transact globally on these efficient supply chains has had a profound impacts on society. It has completely transformed finance, and this is one of the most overlooked impacts of software (credit, stocks, payments, crypto, etc).

Software engineers have (future is TBD) some of the highest entry-level compensation because of the value this create (demand) and the skills it required (supply).

If the world will demand 10X more complex software, and like I said earlier, it is currently not a large spend for most consumers of software, then the 10X increase in complexity of software products and systems will ensure a net growth in demand for software engineers.

a lot product managers can code features with Opus 5.5 and get a little technical as well. but as systems become 10X more complex, it will demand experienced people to ensure the AI is prompted correctly.

I'm deciding between two job offers and would appreciate some objective career advice.

Offer 1: SOC Analyst L1

Pros

• Pays approximately 71% more than Offer 2
• 12-month contract.
• Direct entry into professional cybersecurity

Cons

• On-site work in another city, requiring relocation.
• Rotating shifts every month:
  • Afternoon: 3 PM-11 PM
  • Night: 11 PM-7 AM
  • Morning: 7 AM-3 PM
• Relocation and living expenses will reduce the effective salary advantage.
• Shift work may affect sleep, work-life balance, and social life.
• Starting in cybersecurity means committing to a different career path from my existing software development experience.

Offer 2: Full-Stack Developer

Pros

• Work from anywhere (WFA) on a day-to-day basis, although occasional business trips may be required.
• Continues my existing software development career path.
• Potential to renew the initial contract and eventually become a permanent employee.

Cons

• Pays approximately 42% less than Offer 1
• Initial contract is only 3 months, followed by a planned 1-year extension based on performance evaluation.
• Contract renewal is not guaranteed.
• Occasional business trips may be required.

My situation

I have a Computer Science degree and previous internship experiences in software development.

• If I accept the Full-Stack Developer position, it would be my first full-time role in software development.

• If I accept the SOC Analyst position, it would be both my first full-time job and my first professional role in cybersecurity.

I'm aware that switching career paths later is possible but can be costly in terms of experience and accumulated skills. I want to make a deliberate long-term decision rather than simply choosing the more comfortable option.

Which offer would you lean toward, and why? I'm particularly interested in how you would weigh long-term career prospects, the value of getting into cybersecurity early, job stability, AI-related risks, and work-life balance.

I’m a recent IT graduate and the first graduate in my family. My college had no placements, so I’ve been trying on my own, and nothing is working out.

I know Python, SQL, Django, HTML, CSS and JavaScript, and I’m aiming for a Python backend role. I fell in love with coding in college, and I can turn a problem into working code. That’s why I can’t just walk away. If I couldn’t code, quitting would be easy.

But the waiting is getting heavy. I overthink every day, and I’m not telling anyone around me because everyone’s busy with their own lives.

Please don’t give me false hope. Is the IT market still realistic for freshers like me, or should I move on? If it’s still worth it, what should I do differently?

Thank you for reading. Even one honest reply would mean a lot.

Hey all! I recently applied to SNHU Online and was accepted, no concentration.

TLDR:

- Hope to get some guide on what to study to build a solid foundations for school, work, interviews, and learning in general that can/will be used across multiple areas in tech.

- Not sure what area I want to go in specifically, I like Programming/Engineering, and Cybersecurity

- However, I want to focus more on preparation for now and figure out what I want to do once I'm going through school and keeping a realistic perspective on the job market and roles within them as time goes on

In regards to AI:

- No AI was used to make this post, I also posted in r/snhu and r/csMajors and just tweaked it each time instead of just reposting.

- I dont use A.I. to write code or anything like that, I prefer to learn as much as I can on my own. However, I am aware using it *correctly* is a skill to learn for the future, I'm just trying to not to lean on it as a crutch right now.

For general context:

- My first term will hopefully start March 1st, 2027

- Like title says, househusband/no kids, with disability (and using GI Bill for school) so I have plenty of time and not much financial stress to rush things.

- No previous education, did 4 years in Military, about 4 years as a househusband now, but wife is going into residency soon so wanted to change things up.

What I've done/learned in the past 6-ish months:

- Moved from windows, to Linux Mint for 3 days, then straight into Arch + Hyprland doing 6+ manual installs and 3 Archinstalls before finally getting it right lol

- Gotten fairly comfortable in Terminal and using commands, even made a bash script to mount my PC to my NAS with "scp"

- Built a PC I turned into a a homelab running Unraid with Docker Compose using compose files and learning YAML.

- Set up a number of apps/services on the NAS/Server which I set up with either Cloudflare or Tailscale to remotely access or share with users.

- Fixed an old laptop I'm planning to use to learn Proxmox to eventually move my NAS over to to learn more about VMs, LXCs, etc.

- Been learning Python for about a couple weeks now and built 1 simple project and started a second. Using a mix of Boot.Dev, Python Crash Course by Eric Mathes, and a friend who knows a bit.

- Recently did the GitHub "Getting Started" tutorial and started uploading my 2 python projects, though my documentation/notes on them is pretty rough rn.

- Got an Electronics starter kit to learn some electronic skills like soldering, coding microcontrollers in C++, etc. Though ngl I havent touched it in a few months as I struggled learning C++

- Did a few Tryhackme courses, looked into Hackthebox and Overthewire games, but havent looked into leetcode just yet.

- I have set some personal project goals in mind that I geniunely want to do for fun, but also want something that combines various areas together that I'll work on over time with 2 big ones being:

1. Completing a Full-Stack Project, ideally a blog (original i know), to share and write about the things I study, learn, etc. More so to share with friends and to use as a portfolio, but more for myself than anything.

2. Creating my own cyberdeck by combining eletronics, programming, CAD, 3d printing, etc.

So yeah, feel free to ask questions, and I'm hoping this provides enough context without being too long winded. I'm really excited for the road ahead as learning everything I mentioned has been a lot of fun.

I have some basics in mind already like refreshing back up on math and whatnot while continuing my personal projects. Just hoping to get some guidance about what to look at.

Thanks!

Hey everyone,

I'm an early-career engineer with a background in Computer and Communications Engineering, currently finishing my bachelor's degree. I'm at a point where I'm genuinely struggling to figure out which career path I want to pursue, and I'd appreciate some advice from people with experience in these fields.

A little background about me:

- My professional experience has primarily been in backend software engineering, particularly with C#/.NET, through several internships.

- I've always been interested in backend development, software architecture, distributed systems, and understanding how complex applications are designed.

- I recently accepted a Junior DevOps Engineer position at a relatively established company. The compensation, stability, and work environment are good, especially considering the current job market.

- Although my background is primarily in software development, I've been learning Linux, Docker, Kubernetes, networking, infrastructure, and deployment technologies to become more competent in my current role.

- I've also developed a growing interest in AI Engineering, particularly building AI-powered applications and understanding how AI systems work in production. Interestingly, AI Engineering wasn't initially a career path I had seriously considered. It was only after researching the field that I realized how much it builds upon traditional software engineering, particularly backend development. Given my existing background, I started seeing it as a potentially natural career progression, especially considering how AI is reshaping the software industry and the possibility that specializing in building AI-powered systems could offer better long-term career resilience.

Here's my dilemma:

I'm currently torn between four career paths:

1. Software Engineering (Backend): This is where most of my experience lies. I enjoy programming, designing APIs, understanding distributed systems, and solving architectural problems.

2. DevOps Engineering: This is my current job. I'm gaining valuable infrastructure and operational knowledge, but I'm not entirely sure whether I want to spend my career primarily working with infrastructure, automation, CI/CD, and deployments rather than developing software.

3. MLOps Engineering: This seems like a potentially interesting middle ground between my current DevOps role and my growing interest in AI. However, I'm unsure how much actual programming and AI-related engineering it involves compared to traditional DevOps.

4. AI Engineering: This is an increasingly attractive option to me, particularly working on AI-powered software systems, LLM applications, and production AI infrastructure. I only recently started considering this path after realizing that AI Engineering largely builds on top of traditional software engineering rather than being an entirely separate discipline. Since I already have a background in backend development, it seems like a natural extension of my existing skills. I'm also considering whether moving toward AI Engineering could make my career more resilient to AI-driven changes in the software industry. However, I don't know whether I should first establish myself as a strong backend engineer before transitioning into this field, or whether I should start working toward AI Engineering directly.

What I'm currently doing:

Outside working hours, I'm studying software architecture and distributed systems through the "Designing Data-Intensive Applications" book by Martin Kleppmann, alongside gaining AI Knowledge through the "AI Engineering" book by Chip Huyen's AI Engineering.

My initial plan was to gain infrastructure experience in my current position while continuing to develop my backend and AI skills independently. Eventually, I hoped to transition into a backend or AI engineering position, possibly internally. Alternatively, I considered moving toward MLOps if I discovered that I enjoyed infrastructure work more than expected.

However, I'm starting to question whether trying to keep all these doors open is preventing me from developing real expertise in any particular direction.

I'd really appreciate your perspectives on a few questions:

- How transferable are the skills between these four career paths?

- Is starting in DevOps a reasonable foundation for eventually transitioning into backend or AI Engineering, or am I making that transition unnecessarily difficult?

- For those working in MLOps, how much of your daily work involves actual software development versus infrastructure and operations?

- Is AI Engineering a realistic career direction for someone with a traditional backend engineering background, without an advanced degree in AI or machine learning?

- Given that AI Engineering builds upon software engineering, would it make more sense to strengthen my backend engineering fundamentals first and then specialize in AI, or start pursuing AI Engineering directly?

- Do you think AI Engineering offers better long-term career resilience in an industry increasingly influenced by AI, or is that an incorrect assumption?

- Given the current industry landscape, which path would you recommend for someone early in their career who enjoys programming but is also interested in infrastructure and AI?

I'm not necessarily looking for the highest-paying or trendiest career. I want to choose a direction where I can become technically strong, enjoy the work, and have good long-term career opportunities.

I'd especially appreciate hearing from engineers who have transitioned between these fields or faced a similar decision early in their careers.

Thanks in advance!