Meeting Title: Brainforge x Naresh Gali Interview Date: 2026-04-02 Meeting participants: Naresh Gali, Kaela Gallagher
WEBVTT
1 00:00:06.420 ⇒ 00:00:07.190 Naresh Gali: 3 more seconds.
2 00:00:10.570 ⇒ 00:00:11.460 Naresh Gali: Super quickly.
3 00:00:11.780 ⇒ 00:00:12.620 Naresh Gali: I don’t want to…
4 00:00:25.940 ⇒ 00:00:30.609 Naresh Gali: But one day I learned it. We shared work.
5 00:00:31.020 ⇒ 00:00:33.300 Naresh Gali: That’s airplanner.
6 00:00:33.920 ⇒ 00:00:35.670 Naresh Gali: His birth is elapsed.
7 00:00:35.840 ⇒ 00:00:42.570 Naresh Gali: Kingston.
8 00:00:43.720 ⇒ 00:00:45.090 Naresh Gali: Jesus Christ.
9 00:00:47.210 ⇒ 00:00:47.940 Naresh Gali: Sweet.
10 00:02:07.090 ⇒ 00:02:08.110 Naresh Gali: from which…
11 00:02:14.240 ⇒ 00:02:20.280 Naresh Gali: Homebone.
12 00:02:23.230 ⇒ 00:02:23.976 Naresh Gali: That’s true.
13 00:02:50.640 ⇒ 00:02:52.419 Kaela Gallagher: Hey Naresh, how’s it going?
14 00:02:53.070 ⇒ 00:02:53.979 Naresh Gali: Hi, Kayla.
15 00:02:54.830 ⇒ 00:02:58.640 Kaela Gallagher: Thanks for taking some time for me. How’s it going?
16 00:02:59.180 ⇒ 00:03:01.080 Naresh Gali: Yeah, it’s getting good. How about you?
17 00:03:01.450 ⇒ 00:03:05.290 Kaela Gallagher: Doing well. Doing well. How’s your day going so far?
18 00:03:05.640 ⇒ 00:03:06.830 Naresh Gali: Yeah, it’s good.
19 00:03:07.750 ⇒ 00:03:09.860 Kaela Gallagher: Good.
20 00:03:09.860 ⇒ 00:03:18.480 Naresh Gali: Yeah, I submitted for an analytical analytics engineering position, so I guess you got my regime through that, right?
21 00:03:19.400 ⇒ 00:03:23.659 Kaela Gallagher: Yes, yeah, and I have your LinkedIn in front of me as well.
22 00:03:23.660 ⇒ 00:03:39.319 Naresh Gali: Yeah, so… so I’ve gone through the site, and, like, I saw 3, almost 3 positions, 3 to 4 positions are, looking for the data plus AI, so… so my profile will definitely work to you guys.
23 00:03:39.870 ⇒ 00:03:44.359 Kaela Gallagher: Okay, awesome! Yeah, I can tell you a little bit more about the roles that we’re hiring for.
24 00:03:44.360 ⇒ 00:03:44.760 Naresh Gali: No.
25 00:03:44.760 ⇒ 00:03:53.689 Kaela Gallagher: In a second, I think I had initially, maybe even reached out to you via LinkedIn, and, yes.
26 00:03:54.050 ⇒ 00:04:00.900 Kaela Gallagher: Yeah, I guess just starting off, like, would love to learn what is making you interested in a new role.
27 00:04:02.310 ⇒ 00:04:06.979 Naresh Gali: So, currently, my project is ending, so that’s why I’m looking for, different roles.
28 00:04:07.490 ⇒ 00:04:12.310 Kaela Gallagher: Okay, and is that the project with, SEPL AI?
29 00:04:12.310 ⇒ 00:04:12.980 Naresh Gali: Yes.
30 00:04:13.180 ⇒ 00:04:19.379 Kaela Gallagher: Okay, okay. Was that, like, a contract position, so now it’s just ending? Yes. Okay.
31 00:04:19.380 ⇒ 00:04:21.259 Naresh Gali: Yeah, that’s just our contractors.
32 00:04:21.540 ⇒ 00:04:25.549 Kaela Gallagher: Okay. What kind of, like, projects were you working on with them?
33 00:04:25.550 ⇒ 00:04:33.400 Naresh Gali: So, like, I’m fine-tuning the LLMs for, based on the data, like, for data analytical roles, so…
34 00:04:34.770 ⇒ 00:04:43.940 Naresh Gali: for, our… our client is, like, a charge GPT, so we do fine-tuning the LLMs based on, RAG vector searches, and then,
35 00:04:44.040 ⇒ 00:04:49.599 Naresh Gali: SQL based on the insights, and then, end-to-end, scenarios.
36 00:04:51.060 ⇒ 00:04:57.469 Kaela Gallagher: Okay, okay, got it, so very, AI-focused, for sure.
37 00:04:57.470 ⇒ 00:05:08.619 Naresh Gali: Because, like, I’ve been in the data for almost 5 plus years, right? So they needed a data guy who can fine-tune the LLMs in the data analytical roles, so… so that’s why I helped them. So…
38 00:05:09.410 ⇒ 00:05:19.329 Kaela Gallagher: Okay, okay, great. And for your next position, are you looking for, like, an analytics engineer position, or what’s most important to you in your next role?
39 00:05:19.890 ⇒ 00:05:39.999 Naresh Gali: So, next role, I’m mostly, looking into where I can use, AI skills in the data. So, my primary focus is always the data. So, I’m a data guy. I’ve been in the data for around 5 plus years, so I… I moved the data from, multiple, legacy systems to the neoliberal system.
40 00:05:40.000 ⇒ 00:05:44.600 Naresh Gali: I handle the whole inventory modules, and then, like, I handle the,
41 00:05:44.600 ⇒ 00:05:55.380 Naresh Gali: to build microservices. So, I’m totally the data guy. So, as of, like, right now, I’m, I’m believing, like, enterprises are almost, like, adopting
42 00:05:55.380 ⇒ 00:06:03.250 Naresh Gali: So I believe, like, 2026 is all about adopting AI into the enterprises. So, so I did, so I’m, like.
43 00:06:03.510 ⇒ 00:06:12.870 Naresh Gali: more interested in bringing AI skills into the data analytical… data analytics, so… Okay.
44 00:06:14.110 ⇒ 00:06:21.860 Kaela Gallagher: Cool. I’m curious, in this role, or maybe in previous roles, have you
45 00:06:22.150 ⇒ 00:06:24.920 Kaela Gallagher: Worked with clients directly at all?
46 00:06:26.200 ⇒ 00:06:37.820 Naresh Gali: No, I didn’t work, clients directly, so I work for Cognizant, so my cli- Cognizant is my employer, and then I work for AliWise, so…
47 00:06:38.820 ⇒ 00:06:45.439 Naresh Gali: Yeah, I work with… I didn’t work with her directly. I didn’t work with clients directly.
48 00:06:45.870 ⇒ 00:06:48.080 Kaela Gallagher: Okay, okay, got it.
49 00:06:48.080 ⇒ 00:07:06.379 Kaela Gallagher: I will say, working with clients directly is definitely very important to us. Because we are a small team, we’re about 25 people right now, all of our engineers are on calls with clients and often, like, directly interfacing with them and solving problems.
50 00:07:06.380 ⇒ 00:07:13.789 Kaela Gallagher: So, at this point in time, I would say that is something that we are looking for for our engineering roles, but…
51 00:07:13.840 ⇒ 00:07:25.120 Kaela Gallagher: I can definitely keep you in mind in the future as we continue to grow and, potentially we hire, like, more account executives and our engineers,
52 00:07:25.310 ⇒ 00:07:30.009 Kaela Gallagher: maybe take a step back from working with clients, I can definitely let you know, and…
53 00:07:30.110 ⇒ 00:07:33.619 Kaela Gallagher: We might have a role that fits a little bit better at that time.
54 00:07:34.920 ⇒ 00:07:35.610 Naresh Gali: Okay.
55 00:07:36.680 ⇒ 00:07:48.360 Kaela Gallagher: Okay, cool. Well, I really appreciate you taking the time to chat with me today. It was great getting to know a little bit more about your background, and yeah, we can stay in touch moving forward.
56 00:07:49.310 ⇒ 00:07:53.449 Naresh Gali: Yeah, just let me know if you are interested in my profile so that I can help you out.
57 00:07:53.850 ⇒ 00:07:57.250 Kaela Gallagher: Okay, awesome. Thanks so much for your time, Naresh, appreciate it.
58 00:07:58.180 ⇒ 00:07:59.469 Naresh Gali: Yeah, thank you, Ken.
59 00:07:59.470 ⇒ 00:07:59.860 Kaela Gallagher: Alright.
60 00:08:00.680 ⇒ 00:08:02.020 Kaela Gallagher: Thanks, bye.