How To Get An AI Job in 2026-27

0:00Hello all, my name is Krish Naik and welcome to my YouTube channel. So guys, today in this specific video, I am going to talk about how to get a job in AI, specifically in 2026, 2027. It's a very simple video. Uh as you all know, AI is evolving at an amazing speed, okay? Many people are worried whether they will be able to crack things. How will they be able to

0:28crack? All these things I will be talking about this in this specific video. Uh before I go ahead, you know, please keep your 20 minutes reserved, not more than 20 minutes, because the things that I'm actually going to share is really, really important and it will definitely be very helpful for you. So keep your 20 minutes free completely

0:51and focus on the entire video. I will be talking about things because every day I see amazing offers people are getting, okay? It's not like hundreds of offers there every day, but yes, there are people who are getting good jobs. And I will also show you the screenshot with respect to that. And then when I talk to them, right? I get to know amazing things, like how did they interview go, how did they prepare, right? So based on that, I have actually created this 20-minute video. I'm

1:22planning to create this 20-minute video. It may go more than that. And I will specifically talk about all the important things that is actually required, okay? So before I go ahead, I'll just go ahead and share my screen. And here you can see, I also have a group. Every day we get tons and tons of uh job offers. So here you can see one of the messages, the screenshot is there. And then if I go over here, you can see over here also, in our platform in WhatsApp and LinkedIn, we continuously get things. So here you can see, I'd like to share a job, got the a with 100% hike. You know, this is

1:57not made up, guys. This is from my portal. Okay, and the LinkedIn other platforms. So, here also you can actually see with the name everything. Then, here also you can actually see landed AI/ML from geography background. This is another one amazing thing, right? Uh one more amazing job offer from here. You can see here, right? And keep on the

2:18people keep on sharing things, right? So, like that there are many many different kind of uh messages that we specifically get. But, here my main focus is to talk about how to get jobs, what all things you really need to do, uh how you need to do, everything I'll be talking about it, right? As you all know, it is true. It is definitely true the AI job market is changing rapidly. Every day there is a requirement of something else. Every day something new is actually coming. And there is no other way. You need to keep on getting yourself updated. Okay? This is one of the very important thing,

2:57right? So, the first thing that I talk about whenever I talk about AI jobs, uh what should you really be focusing on and all, right? Um you know, I'll just give you very simple thing, okay? First point is that choose the choose the right AI role, okay? Right AI role. Choose the right AI role, okay? Now, what does this basically mean? So, like this I will be creating multiple

3:31points, right? Choose the right AI role. So, let's discuss about this, right? Specifically right now, based on the job market that is considerably changing, right? Every day. The right now there are three main important roles that you can actually focus on. Number one, AI engineering. AI engineering. So, AI the second role is about

3:56AI FD. And the third one more very important role is related to AI ops LLM ops ML ops, right? Now, considering this the first role is very simple AI engineering role, which you may be familiar with. AI FD is nothing but forward deployed engineer. Forward deployed engineer. Right? This is my next role. And this is

4:31your AI platform engineer. Platform engineer. And this role is also picking up. Right now, it is very much in demand. This is actually required, right? Very specifically focus on AI ops, LLM ops, and ML ops, right? Now, AI engineering role how do you probably go ahead and differentiate it or which one should you

4:57actually consider? Right? What role should you actually consider? It completely depends on you. Right? AI engineer role anybody who is right now involved in building AI agents, agentic AI applications, or any kind of product that is specifically you know, solving some kind of problems. You are using LLMs. You are using AI agents. You are building rags.

5:24Right? That all kind of roles comes over here. AI engineering, right? So, that basically means you in the case of AI engineering, you are very good at coding. You know how to build application, how to develop applications. And whether you are a fresher experienced person, right? You are specifically into the tech field, right? Tech part of the things that is required. So, this is a really like let's say you start with software engineering, you probably go ahead and now become a data scientist, then you become a soft AI engineer, then probably in the future you become a solution architect. So, everything kind of specific technical roles

6:05actually goes with respect to AI engineering. Here, your main focus is to build, right? Build. Now, as timeline comes, right? Before used to build applications, now probably you are building AI agents, you are you are building rag application, you are building agentic rag application, you are building something else, right? So, if you are specifically interested in the technical field, I would suggest

6:30you focus on the AI engineering, right? If you are a fresher, you want to get into the technical field, go into AI engineering, right? This is more about here, you actually use coding agents, right? You build you build the entire application with coding agents. Along with that, you try to learn about, you know, orchestration, you try to learn about um some of the agentic frameworks, common agentic open-source frameworks. But here, your main work is basically to build. Okay? Build a AI agent, build a

7:05rag application, only build. Okay? Second important thing is that and in in the case of AI engineering, you should also have, if you are experienced person, you should definitely have knowledge with respect to deployment and orchestration, inferencing, many more things, right? Now, with respect to the deployment, you should also be considering the important info related to the security, right? Security. Let's say you are building an AI agent, how do you run that AI agent within a within a guarded environment? You have guardrails, you have eval frameworks, you have observability, you have many more things as such, right? So, all those things are also there. So, a good

7:41technical person will be that he will try to understand the entire life cycle of the modern software development life cycle with the help of wipe coding agents, like basically the coding agents, where you do wipe coding and along with that you you basically know how to probably take that entire application into production. So, that can also be the part of AI engineering if you are very highly experienced, right? But if you are within first two five to six seven eight years, you basically focus on building the application in short, right? Now, this is one more role which is becoming very

8:14very popular, that is called as AIFD. That is forward deployed engineer. Now, who can actually come to this role? This role is more about working in the client location, right? Client location. So, here you can basically say that this is a role as in with the combination of a solution architect, solution architect, plus

8:40a product manager. Plus a product manager, we basically say it as PM, right? Product manager. So, a product manager specifically sitting in the client location, understanding about the legacy system that they have actually built, and then trying to build an application and taking the help of their team to showcase that how they can actually become an AI enabled, right? In a Basically, how they can actually bring AI integration into their product. Let's say the client is there, they are working on a product that is

9:16currently in the legacy system, right? And now they really wanted to use LLMs, they want to probably understand how they can also use all this kind of AI agents within their application, then an AIFD, that is forward deployed engineer, will actually help you to do that, right? Before also, there were roles, there were roles like product managers and all, who used to understand the requirements. There were business analysts who needs to understand the requirements and tell those information to their team. But here you can understand, it's more like a technical plus uh management kind of role. But here the management is more about understanding

9:53the systems. They definitely have a lot of technical knowledge. And again, this is basically applied for uh highly experienced people, at least 10 plus years of experience, right? Uh And again, I'm telling you that only 10 plus years will not be just getting applied, even though you are 5 plus years of experience, even though you have talent, even though you are 2 plus years of experience, it's all about how is your previous work experience and what kind of role you have actually

10:19done. See, in AIFD also, you may have a very highly experienced person. Under him, you may have uh 5 plus years of experience or 2 plus years of experience, like that. But understand, it's more about communicating with the client, getting to understand about how the legacy system works, and how you can actually make them AI-enabled, right? So that is more about AIFD. Now the third

10:40role is about AI Ops, LLM Ops, ML Ops. So in short, this is like a combination of AI plus DevOps, right? How do you take your AI to production, right? There are three important things, right? With respect to taking AI to production, right? One is whatever application that you build. Let's say you're building AI agents, right? How you're managing this AI agents in

11:03production. With respect to scalability, with respect to security, everything. How you are managing them, right? Second is if you're using any kind of LLMs, right? How you are managing LLMs also, right? Let's say if you're fine-tuning LLMs, how do you go ahead and deploy it? How do you create an inferencing engine? Everything. Yes, designing and all, you can see that AI engineering team and AI Ops team will definitely be helpful, right? But if you probably consider

11:31these three important roles, right? Let's say this three important roles, AIFD You can just consider in this way, right? So, I will just go ahead and So, let's say this is your AIFD who sits towards the client location. They get to understand about things. They keep on communicating with the AI engineering team. They can communicate with the AI engineering team with respect to implementation. If they really want to take it into production, they can also go ahead and communicate with the AI

11:59platform. Right? So, this kind of communications will keep on happening and you can see some of the skill sets will definitely overlap. If you consider with respect to cloud work, with respect to CICD, with respect to scalability, with respect to designing what machine or deciding what machine to probably consider, right? Everything you can probably see they will be decided by the AI platform engineer. But in case of AI engineering here, design, building application,

12:31everything. Building application, architect, right? Everything can be understood over here. In case of AIFD, understanding the legacy system, what more compliances are there with respect to the uh client product, right? And how they can actually make this into AI enabled, right? So, a kind of discussion definitely happens with respect to all these things, right? So, this is the first step. You need to choose the right role and based on that and that is completely your requirement, which role

13:01you really need to go ahead with. Whether you want to go ahead with AI engineering, AIFD, or AI um AI ops or LLM ops or ML ops, right? So, once you have decided like which role you are specifically targeting, if you're a fresher or you want to probably get into technical, AI engineering should be the thing. If you're experienced, you like communicating, AIFD is the role that you really need to target. If you You really interested in understanding about the platform, how to make it production ready, you know, do the part that is specifically like CICD, AI Ops, LLM Ops, and ML Ops. That is a

13:35part of a AI platform engineer. If you're into DevOps, definitely this is the role. Now, the second thing is that you need to learn skill sets based on the specific roles, right? Skill sets. Like say, if I want to become an AI engineer, I will learn about Python, APIs. I will probably learn about LLMs, Transformers. So, I'll try to go ahead and see with respect to rag. Uh I'll see about you know, understanding about different different frameworks, uh how to apply LLM evaluation, guardrails, observability, and all,

14:05right? If I talk with respect to AI engineer or if there is a role with respect to AI engineer and AI platform engineer, that is related to system design. I can also go ahead and probably go ahead and check with respect to system design of AI, specifically AI. Okay, AI system design. And soon we are also going to start this particular series in our sessions, you know, in our YouTube channel also you'll be able to see that series related to AI system design. And the best part is that you learn all these things by building projects. That way you'll be able to get more idea, right? So, the second important thing is

14:40that run learn the skill sets, right? What is specifically required? Learn the hottest topic that is currently going on. Learn how to build an AI agents. Learn how to build an agentic AI application workflows. Learn how to apply LLM evaluations, right? LLM evals. Learn how to apply guardrails, right? Learn about observability, right? These are some of the very important topic,

15:05right? Uh the with respect to the skill sets. Now, specifically with respect to the demand of the role, you need to update your skill self with the skill sets, right? In case of AIFD, obviously you really need to be a good communication communicator, right? You really You to be good to You need to understand about the problem statement. A 360-degree

15:24knowledge context is basically required. Okay. Now, coming to the third one and and the skill sets I've also uploaded a lot of road maps. What skill sets I also have free AI tutorials in my channel. You can also go ahead and check it out. Now, coming to the third most important thing and this is something really, really important and many people misses it,

15:43right? What exactly it is? Build projects. Now, when I'm telling build projects, build very strong project, right? Very strong project. And this project should follow definitely the current software development life cycle, right? New software development life cycle. Now, what is the new software development life cycle? First, you should be using a coding agent to write the code,

16:11right? Then, after using the coding agent, how do you upload the static memory? Like what kind of information you get with respect to the static memory? What all things needs to be uh reserved with respect to skills? What all skills you really need to create? What all skills you can actually use from the internet, right? Then, how do you go ahead and build your application,

16:30right? How do you make sure to provide human approvals where all human approval is specifically required? Then, you talk about unit test cases, right? This is how we specifically use, right? If we are using coding agents, there are a lot many things, right? So, software development life cycle again, I've made a dedicated video on understanding about software development life cycle. So, by using this new software development life cycle, how do you build a very strong project? Now, whenever I talk about strong project, people think that, okay, build an end-to-end

17:05run it in your local machine, that's it. No. When I say an end-to-end project, it should be at least a kind of enterprise grade, right? Enterprise grade. Production grade, enterprise grade. Why do I say this? Because tomorrow you go for the interview, tomorrow you go ahead and just see anything, you see what people are actually showcasing, right? The kind of projects you'll be able to explain much more in a better way to the interviewers, right? So, let's say I go ahead and build an RAG application. I will just not go ahead and build a simple RAG application, right? I will make sure that in this RAG, you know, how do I probably

17:44go ahead and use uh you know, some kind of evaluation frameworks. Some kind of guardrails, right? Some kind of securities, right? Then I go ahead and see that how these all things are actually deployed. I will just go ahead and explore. I will I will try to make it a kind of things over here is that that matters right now in the industry, right? AI agent, agentic workflows. How do I probably go ahead and build

18:16everything, right? And nowadays it is becoming very much popular wherein you'll be able to see a lot of open source projects just they're deploying in the GitHub and they people are making it very very popular, right? Some of the open source projects I'll talk about reverse engineer anything. That has become really popular right now. Everybody is probably using and the fundamental is very simple. They are using coding agents, they are using

18:42LLMs, everything. Here, the main idea is basically to replicate any kind of product that is available in the internet, right? Specifically software application. So, whenever I talk about enterprise grade application, you should be thinking that what is currently right now in the industry trend and based on that what kind of product is there. Because tomorrow you go for the interview, you will be able to explain them very well, right? Then you also

19:06talk with respect to deployments, right? Not you you're just not saying that, "Hey, I just have to build this." Hardly it'll take 5 minutes with the help of coding agents. But, how do you take this entire application into production? That is the most important crucial thing. I don't want 50 projects. If you are able to just build one strong project with everything implemented, then building other things becomes very very easy. Right? I'd also like to see some of the projects which may have

19:36multi-agent workflow. Multi-agent workflow. So, project one, you take it, build it so strong that you have got to know about the entire new software development life cycle, right? Everything you basically know about it, right? So, that way, anytime you go for the interview, you will be able to explain them well properly. Okay? Then, the fourth important step.

20:03Make your work visible. Make your work visible. Right? If you are able to do this, guys, from the internet, many people will contact you. Right? Those were the days that those days are gone where you just go ahead and apply your job in Naukri or LinkedIn. And you wait for people to reply you back. No. If you want to make your work visible, you know, make your projects open source. Make it share it everywhere wherever you like. Post about the work that you have actually done. Try to talk about it like what kind of ideas you

20:39have implemented in it. If somebody's basically seeing that and if they find it really important, trust me, they're just going to go ahead and reach out to you. So, making your work visible is super important, guys. Without this, trust me, no one will know you. There are so many people who knows to do amazing things, but there are very few people who get into the right position with the the right kind of work. So, you really need

21:03to showcase your work everywhere, right? Then, uh the last thing is that, you know, definitely try to ask for referrals wherever you see people like you, you know, who are specifically interested in building something. If they're interested over there, please go ahead and just uh reach out to them. Ask for referrals. Uh there are amazing startups that are currently going on, right? Go ahead and see see amazing startups in Product Hunt, you know, directly contact the founders if you want. This is the recent trend, you know, those days are gone where you just go ahead and apply in Naukri or LinkedIn and wait for the reply. Now you have so many amazing

21:41things, right? There's so many startups that are coming up in the companies in everywhere like they're posting in Product Hunt. Go ahead and contact the founders. Use ChatGPT even. Which are the new trending AI startups that are there? When they are starting fresh, right? They will be requiring people. They will be requiring people who knows how to build things. And try to pitch them in LinkedIn. Show them the kind of work that you are actually doing. And just go ahead and paste your GitHub. Paste your kind of products that you have actually built,

22:11right? I have seen this. I've contacted so many startups. I'm just trying to understand what kind of work they have done, you know, and everybody's basically happy to talk about their products, what they are actually building. You should also bring your points like how you can actually help them. All these things, right? So definitely go ahead and explore all the amazing AI startups, what all things are

22:31basically going on, right? Uh one very important thing is that there is a recent system design AI system design thing also that is coming up. And that is still fresh right now. People, companies are looking for people who can actually understand the AI system design. Uh take their AI agents to production, how efficiently they can actually do that. Try to see all the things that are currently trending right now, right? And based on that you can

22:56keep on applying. Okay? I know sometimes [clears throat] uh people say, "Sir, there is no job. We're still trying to do it." Guys, there is a process we need to keep on iteratively try harder and harder. Try to see wherever the opportunities are basically coming up. Try to see that how we can also apply our skill sets

23:16everywhere. There are people made for anyone out here. Always there is a requirement. You just need to go ahead and find it. You need to be eager. Uh but definitely follow these four important steps that I've actually told, right? It will be very, very helpful, right? So, yeah, this was it from my side. I'll see you in the next video. Have a great day. Thank you all. Take

23:35care. Bye-bye.