[00:02] Python and suddenly after 4.6 release my skills have no value. Everyone see AI as a magic but it is just a tool. So I need to now start how can I unlearn a few things? How can I remove the baggage I'm carrying as a
[00:16] remove the baggage I'm carrying as a developer? AI services company and we have a team of AI engineers here. Today I'm going to show you a day in the life of an AI engineer.
[00:38] involvement here is in sales, dealing with clients and [music] participating in the technical architecture for AI projects. I also do video shooting for my code basics work right from this office. The AI engineering team sits in
[00:54] the [music] next office so we are going to walk over there. Let's go.
[01:14] Srikanth, you want to introduce yourself? Yeah, sure. My name is Srikanth Dongala and I'm working as an AI engineer at Atli Technologies. Okay. So we would like to know what kind of project you are working on and what
[01:28] there are a lot of projects that I'm currently working on but one project to pick is in the fintech domain. [music] So which is about analyzing the spending
[01:40] patterns of a customers and then helping them to [music] improve their credit score, credit insights and then building recommendation engine so that they see the actual products that are highly relevant to their spending nature and
[01:53] spending patterns. So this is in the fintech domain. Okay. And what kind of here? Most of the things back end is in Python Python and for the cloud we are using AWS.
[02:06] And we'll have a load balancer and lambda functions and we are using Fargate to manage all the load and concurrency handlers. So this is mostly and we also use Docker, we'll use Postman, you know. And in terms of LLM
[02:21] like which LLM do you use here? >> So we use OpenAI and also we are now recently testing the server models to test the capabilities of Indian models and see how Oh, wow. That's pretty amazing. Okay. [music]
[02:34] I want to know how does your day look like, typical day look like from morning till evening? These days [music] my day starts around 7:00 or 8:00 a.m. >> [music] >> collecting most important resources that
[02:48] I want to you know do research on or to look into for that particular day. released, right? Yeah, it is very difficult to you know catch up with everything but you'll have to try to do as much as you can. Yesterday I started
[03:00] up Open Claw and when I was on second step I I heard a news about Nemo Claw, right? Which Nvidia released in their GTC. It's crazy. >> So it's difficult to you know catch up everything but we'll have to try as much
[03:16] as we can. So I will start my day with you know identifying what all things that I need to cover for for that day and I will take short break for 1 or 1 and then I'll be back in office by around 9:30 or 10:00 ish and then the
[03:29] very first thing I do is check my emails and messages and I will complete that routine for about 5 or 10 minutes and then I will start planning my day, what particular day. And once I do that planning I will pick
[03:45] that particular day because in the morning we'll be fresh. Oh, that's a >> So we I will you know start with the most challenging task for that >> [music] >> and in parallel we'll also having some
[04:00] internal you know team sync ups and scrum calls. first half. And I will try to keep most of the calls in the second half of the day because you know to make most of to you know
[04:14] So in the second half we'll be having some scrum calls, internal sync ups and again these are the days where we alone can't happening, right? So we have some internal sessions where we'll be you
[04:28] know sharing our knowledge so everyone will be updated on that along with some client calls and everything. Okay and I'm seeing some something interesting like is this like a technical architecture diagram?
[04:40] architecture diagram? Yeah, so this is a basic flow of this particular you know data starting from the ingestion and how we process all the transaction information and how it helps you know generate insights for the users
[04:54] understanding their financial nature, financial patterns and then help us recommending some good products based on the Okay. >> patterns. And in terms of
[05:07] framework do you use LangChain [music] or something else? I use LangChain and again it depends on the use case and then so I also use CrewAI but when I need to you know have multiple [music] you know agents working on then I have a
[05:20] better agent to orchestrate that but as part of the you know framework I'll mostly be using LangChain. Okay. >> And we'll also have LangSmith, LangGraph So how often do you interact with clients? Do you have a separate
[05:36] separate product management team and here they are. Hello. So they are the driving force. Okay. [music] And you have any like timing related situation because most of the clients are based in US and UAE.
[05:52] So you have to take calls in the evening or something? Yeah, so we manage our workload so whenever we want to you know stretch our hours we are going to attend you know calls at the late night, right? So we will manage our day accordingly.
[06:05] afternoon as well. Exactly. And this is our activity area Okay. where we'll be going on, key discussions [music] happening in this area. Okay. So I think we covered till afternoon so how does your day look like after lunch?
[06:21] So after working on the complex task, right? So I need some refreshment so we have we are flexible so in the afternoon I go my home, it is nearby. I'll have my [music] lunch and I will take a break for about an hour
[06:35] and then I will be back in office again. And I will again start organizing my day I will start with the important tasks again, do some coding and complete a few
[06:47] tasks and then we'll also have some internal meetings. So I will try to keep the day. And so after lunch we'll always you know be a bit sleepy, right? So we we have the flexibility to take a nap as well
[07:03] and we have some coffee breaks, we go out to get some refreshment and these these are essential to keep yourself you know refreshed and be active when you're working on something very complex, right? So we have the flexibility and
[07:18] we'll be back to our client meetings or internal meetings at the end of the day and my day ends at around 5:30, 6:00. Okay. Good. Now so I would like to ask
[07:30] been working as an AI engineer for how many years now? Last 3 years. 3 years? >> Yeah. Okay. So you have seen days of statistical ML all the way till GPTs and
[07:43] GenAI, all of that. Many of the viewers who are watching this video will be beginner or they have aspiration to become AI engineer. So can you tell me what is that one mistake that every beginner makes which [music] you might
[07:56] >> Yes. So one thing that any beginner should remember is do not jump to a framework or a technique or a model directly. First understand the problem, brainstorm it
[08:12] and then pick the right solution for that problem because a few problems you can do it with statistics, with ML, with and with GenAI as well. So understand the [music] problem and then pick the right tool that you actually need
[08:25] or any ML. [music] That's what I I usually say like don't marry to a specific tool or technology. Even people say I'm a dot net developer, I'm a Java developer, I it really freaks me out, you know. We live in the vibe
[08:40] coding era. You can code in anything. Yeah. So by the way, since we mentioned vibe coding, how much of vibe coding do you use in your day-to-day work? That's actually a very good point to make and so recently it's like 40 to 40 or 50% we
[08:55] can say for the AI specific tasks whenever we want to create some boiler plates, some pipelines, right? So mostly we use AI tool you know do that we use AI tool you know do that automation and then we use that time to
[09:07] work on some complex tasks. Mhm. So be it architecture, be it in terms of >> [music] >> So we utilize this time that day but if I'm so this is these are the days where we don't spend just on working on AI. So
[09:21] we take additional tasks for software engineers as well, right? So for that I >> [music] >> Okay. It's vibe coding. But for the AI specific it will be 30, 40%. >> 30, 40% and yesterday I noticed one
[09:35] example where we were parsing the document using DocLing for the Rex pipeline and DocLing's default parser has some issue parsing the headers, you know, it doesn't provide the hierarchy
[09:48] >> Now if you're writing code using Claude default. Exactly. [music] But then we went to GitHub, we found that it is a known issue and somebody has provided some solution,
[10:02] some workaround. We ended up using that workaround and that's where we felt [laughter] that as an AI engineer so our jobs are safe because cloud code cannot fully automate it. Yeah. Uh, and it was an interesting perspective that we built
[10:18] while working on this real problem. >> That's great. Okay, so what is the what is the fun part of your day? So it is convincing people what AI cannot do. >> [laughter]
[10:34] >> [music] >> everyone see AI as a magic but it is that you wish for. It has some limitations. It has, you know, its leverage, you know, those strengths and we'll have to back AI up with our human
[10:50] intelligence. So I [clears throat] think convincing people what AI cannot do >> [laughter] >> And how often do you interact with clients? I know that there are product managers but you also interact with
[11:03] clients directly, correct? We do because, you know, there'll be a few technical clients where we will be dealing with them directly and a few projects will be handled by, you know, project managing team but we do interact
[11:15] with clients often. Okay, that takes me to the next question which is how important is a communication skill for any AI engineer? So that is one of the any AI engineer? So that is one of the most important skill because
[11:28] world. And it is our communication, the way we interpret, the way we communicate will client [music] expects only results, right? For that we
[11:43] If we are not able to communicate clearly, that is where miscommunications happen and everything will be, you know, in a tricky. Okay. So that is really important. AI can replace coding but not the communication. So we'll have to
[11:56] mentioned communication and communication is also accompanied by many other skills like convincing people without hurting So do you see these scenarios where you are in a client meeting, there is a
[12:11] non-technical stakeholder, business stakeholder >> and they will do chat GPT and they will come up with technical suggestions? So that's a good point and it actually happened with me as well where I was in
[12:25] one of the client meetings and the product manager he asked, simple. It's based on statistical and rejects. We can >> And then when I explained him this approach, he just questioned me, "Where
[12:39] >> [laughter] >> Okay. So then I'll have to, you know, do some detailed breakdown. I will have I know I did some analysis, >> shown him the numbers, why we didn't why do we don't need that, what's the
[12:51] complexities associated with that. Then he understood, "Okay, let's stick with >> So if you use regular expression they don't like it. Yeah, they want to have AI because they want to have LLMs in their architecture. Okay.
[13:03] Great. So this is one of our meeting rooms happening. And this is one thing that I like the most, whiteboard Okay. because anything that actually goes into implementation
[13:16] part, right? There'll be a lot of brainstorming happening. We'll plan our be happening in this beautiful place. a good point. If you don't have a right architecture, you might go on a wrong
[13:30] something went wrong." And we'll have to, you know, Yeah, you waste a lot of >> In this era of rapid technical advancement, what is one mindset shift
[13:42] that one needs to have if they want to thrive in this new time? So the very first thing I would say is unlearning a few things. Mhm. So I can [music] say I am a developer and I'm very good at Python and suddenly after
[13:57] 4.6 release, my skills have no value. So I need to now start how can I unlearn a few things? How can I remove the baggage [music] I'm carrying as a developer? Mhm. If we don't do that, AI will obviously replace me and we don't add
[14:11] any value additional to that. So [music] whatever the time that we are saving, giving the task to code or the AI, we'll have to invest that time [music] in the critical thinking where we can add some value with the human intelligence. That
[14:24] cannot be replaced by AI. So that is way we'll have to, you know, learn unlearning anything. [music] Okay, that's that's really a very good punchline. We need to learn how to unlearn things.
[14:37] >> Thank you Srikanth for your time today and folks who are watching this video, if you have any questions, please feel free to post in the comment box below. >> Both me and Srikanth will be ready to help you. Our team has worked on more
[14:52] >> [music] >> AI implementations for our clients based >> AI implementations for our clients based in US and UAE and we can share our experience, share some tips based on the knowledge that we have gained so far.
[15:06] Right? [music] Thank you very much for watching. Bye-bye.