Meeting Title: Brainforge AI Engineer Interview Date: 2026-04-29 Meeting participants: Indu Gaddam, Kaela Gallagher
WEBVTT
1 00:01:22.840 ⇒ 00:01:24.300 Kaela Gallagher: Good morning, how’s it going?
2 00:01:24.300 ⇒ 00:01:26.089 Indu Gaddam: Good morning, Gail, how are you?
3 00:01:26.410 ⇒ 00:01:28.489 Kaela Gallagher: I’m doing well, how are you?
4 00:01:28.490 ⇒ 00:01:30.059 Indu Gaddam: I’m good, thank you.
5 00:01:30.060 ⇒ 00:01:47.410 Kaela Gallagher: Good! Thanks so much for taking the time for me today, appreciate it. Yeah, would love to just use this time to learn a little bit more about you, and kind of what you’re looking for next, and then I can tell you a little bit more about, Brainforge as well.
6 00:01:47.410 ⇒ 00:02:03.660 Kaela Gallagher: But yeah, the reason I reached out is, we are looking to expand our engineering team, specifically in, like, the AI engineering space, and specifically within Austin, so that’s how I.
7 00:02:03.660 ⇒ 00:02:05.549 Indu Gaddam: So, oh, coop.
8 00:02:05.550 ⇒ 00:02:08.880 Kaela Gallagher: across your profile. You’re still located in Austin, right?
9 00:02:08.880 ⇒ 00:02:09.780 Indu Gaddam: Yes.
10 00:02:10.810 ⇒ 00:02:19.320 Kaela Gallagher: Okay, cool. Yeah, would love to know, like, a little bit more about what you’re doing now. I noticed you’re interning as an AI engineer?
11 00:02:19.320 ⇒ 00:02:19.950 Indu Gaddam: Yeah.
12 00:02:20.150 ⇒ 00:02:20.940 Kaela Gallagher: Okay.
13 00:02:22.580 ⇒ 00:02:23.330 Indu Gaddam: Sorry?
14 00:02:23.550 ⇒ 00:02:25.030 Kaela Gallagher: Can you tell me more about that role?
15 00:02:25.030 ⇒ 00:02:42.890 Indu Gaddam: Sure. So currently I’m working as an AI engineer at Sophin AI. So, in my role, I focus on building Gen AI data pipelines. So, in this role, basically, I work on processing unstructured data into structured insights, like the documents and the Excels.
16 00:02:42.920 ⇒ 00:02:48.209 Indu Gaddam: So I mainly use technologies like Python, SQL, and Postgres.
17 00:02:48.210 ⇒ 00:03:12.340 Indu Gaddam: Also, to build the RAC system, I use the vector databases, so I use these, RAC pipelines to convert these unstructured, sorry, documents into structured insights. Basically, these are the, financial documents, so, if, investor wants to invest in a startup, then investor comes to our platform, and
18 00:03:12.340 ⇒ 00:03:31.189 Indu Gaddam: uploads the pitch documents or the related documents of the startup, and then we, using our RAP pipeline, we give the insights of the startup, so investor knows what are the red flags, what are the green flags the startup have, and he decides based on those insights whether he wants to invest or not.
19 00:03:31.400 ⇒ 00:03:33.050 Indu Gaddam: So, this is my role.
20 00:03:34.300 ⇒ 00:03:35.820 Kaela Gallagher: Okay, wow, okay.
21 00:03:35.820 ⇒ 00:03:36.380 Indu Gaddam: Yeah.
22 00:03:36.940 ⇒ 00:03:41.489 Kaela Gallagher: And then prior to that, you were in, like, the data engineering space?
23 00:03:41.770 ⇒ 00:04:00.389 Indu Gaddam: Yes. So, before this, I worked as a data engineer, which also combines a little bit of data analyst. So, my major, responsibilities are building data pipelines, automated data pipelines, using, the cloud technologies, like the AWS, Glue, and Athena.
24 00:04:00.390 ⇒ 00:04:12.740 Indu Gaddam: So I worked on maintaining, building and maintaining these pipelines. Also, apart from that, I worked on building the dashboards using AWS Quickside and the TabView.
25 00:04:12.740 ⇒ 00:04:32.369 Indu Gaddam: For the data insights, so that, the teams can use those dashboards to get the insights of the data. So, apart from that, while I’m working on the Amazon, I also build a quicksight dashboard, which, calculates the data delays.
26 00:04:32.370 ⇒ 00:04:44.310 Indu Gaddam: And shows that in the dashboard, so that downstream teams can know what is happening, what are the data delays we have today, and so that they can plan according to it.
27 00:04:45.760 ⇒ 00:04:46.140 Kaela Gallagher: Okay.
28 00:04:46.140 ⇒ 00:04:48.049 Indu Gaddam: This is my data engineering background.
29 00:04:48.050 ⇒ 00:04:53.880 Kaela Gallagher: Okay, awesome. And what is making you interested in a new position right now?
30 00:04:54.290 ⇒ 00:05:10.609 Indu Gaddam: So, I want to focus on the, AI plus data side. So, when I looked at the, roles you have in your career site, so it’s quite interesting that you’re building AI to get the data insights.
31 00:05:10.610 ⇒ 00:05:20.059 Indu Gaddam: So, I’m… like, that really aligns with my current goal, so I want to work at the point where the AI and data meets. So…
32 00:05:20.060 ⇒ 00:05:20.590 Kaela Gallagher: Okay.
33 00:05:20.590 ⇒ 00:05:21.090 Indu Gaddam: Yeah.
34 00:05:21.090 ⇒ 00:05:25.410 Kaela Gallagher: Okay. Are you working on any, like, AI projects outside of work?
35 00:05:26.070 ⇒ 00:05:36.029 Indu Gaddam: I’m… I’m not currently working outside my project, I’m, working on the AI in my current, company for the SOFIN.
36 00:05:36.420 ⇒ 00:05:38.050 Kaela Gallagher: Okay, okay, cool.
37 00:05:38.460 ⇒ 00:05:44.159 Kaela Gallagher: In terms of compensation, what kind of pay are you looking for in your next role?
38 00:05:44.790 ⇒ 00:05:57.889 Indu Gaddam: So, my main goal is to, work in this, as I said, like, AI plus data, so I’m flexible with the compensation. So, yeah, I’m open to negotiate, so it’s fine for me.
39 00:05:58.130 ⇒ 00:06:01.509 Indu Gaddam: Yeah. Okay. With the industry standards of pay, yeah.
40 00:06:02.060 ⇒ 00:06:20.770 Kaela Gallagher: Okay, just a little bit about Brainforge and how we’re structured right now. Our entire team is on a 1099 basis, which is independent contracting, so we are unable to, like, provide any visa sponsorships or anything like that. Curious if that
41 00:06:20.770 ⇒ 00:06:22.309 Kaela Gallagher: Setup works for you.
42 00:06:22.770 ⇒ 00:06:32.179 Indu Gaddam: Yeah, so I don’t need any sponsorship right now, like, I have 3 years of work authorization from now, so I don’t require any sponsorship.
43 00:06:33.110 ⇒ 00:06:33.870 Kaela Gallagher: Okay. Okay.
44 00:06:34.460 ⇒ 00:06:35.819 Kaela Gallagher: So, like, a sim OT.
45 00:06:35.820 ⇒ 00:06:36.760 Indu Gaddam: Yep.
46 00:06:36.760 ⇒ 00:06:40.210 Kaela Gallagher: Okay, okay, cool.
47 00:06:41.630 ⇒ 00:06:53.189 Kaela Gallagher: I think those are the main questions I have for you, just to tell you a little bit more about our positions. We actually just filled our data engineer role this morning. I think…
48 00:06:53.260 ⇒ 00:07:03.680 Kaela Gallagher: you had applied for that position. So the roles that we have remaining would be an analytics engineer position and an AI engineer role.
49 00:07:04.040 ⇒ 00:07:05.670 Indu Gaddam: Yeah, that works for me.
50 00:07:06.060 ⇒ 00:07:06.910 Kaela Gallagher: Okay, cool.
51 00:07:06.910 ⇒ 00:07:14.269 Indu Gaddam: Yeah, so AI engineer, I’m more interested in, like, AI engineer, so if you can do that, that will be more helpful.
52 00:07:14.790 ⇒ 00:07:17.180 Kaela Gallagher: Okay, cool.
53 00:07:17.670 ⇒ 00:07:29.429 Kaela Gallagher: Yeah, in terms of what we’re looking for on the AI side, so definitely somebody that’s, like, really passionate about AI is important to us, because it’s always changing, and we’re always learning and adopting new things.
54 00:07:29.450 ⇒ 00:07:45.549 Kaela Gallagher: Because we are a consultancy and we work with clients, communication is super important to us, somebody that can hop on calls with clients, understand needs, and communicate, really technical concepts in a way that makes sense. Yeah.
55 00:07:45.760 ⇒ 00:08:00.859 Kaela Gallagher: And then we would probably have you on, like, two to three clients at a time, so being able to contact switch and kind of move back and forth easily is really important to us, too. Right now, we’re fully remote as a company, but
56 00:08:00.860 ⇒ 00:08:08.150 Kaela Gallagher: Our CEO is based in Austin, so we would love to have an engineer in Austin.
57 00:08:08.510 ⇒ 00:08:11.100 Kaela Gallagher: Just for occasional, like, in-person meetups.
58 00:08:11.240 ⇒ 00:08:12.250 Kaela Gallagher: Yep.
59 00:08:12.920 ⇒ 00:08:17.969 Kaela Gallagher: And yeah, that’s kind of the overview. Any other questions that I can help answer?
60 00:08:18.170 ⇒ 00:08:28.230 Indu Gaddam: So, can I know, like, so what will be the process of this, interview, and can I expect the next call? So, yeah.
61 00:08:28.490 ⇒ 00:08:42.699 Kaela Gallagher: Yeah, so the process will be 3 steps after this. One is kind of an intro and overview of your experience. The second is more technical. No, like, live coding or anything, but really diving into technical concepts.
62 00:08:42.700 ⇒ 00:08:53.869 Kaela Gallagher: And then the third one, we would give you a take-home challenge ahead of the panel, and you would bring a solution to the panel and present it like you were to, a client.
63 00:08:53.870 ⇒ 00:09:07.849 Kaela Gallagher: So, that’s the overview of our process. For each round, we would send, like, a booking link to you, so, the quicker you schedule those, then the quicker we can move along.
64 00:09:07.930 ⇒ 00:09:21.639 Kaela Gallagher: And then in terms of feedback, I have quite a few calls over the next few days, so I would say you can probably hear back from me, like, early next week on, next steps and if we’re moving forward.
65 00:09:22.130 ⇒ 00:09:23.560 Indu Gaddam: Sure, thank you.
66 00:09:23.560 ⇒ 00:09:27.840 Kaela Gallagher: Okay, okay, awesome. Yeah, any other questions that I can help answer?
67 00:09:27.840 ⇒ 00:09:30.129 Indu Gaddam: I think I’m good, thank you.
68 00:09:30.360 ⇒ 00:09:35.569 Kaela Gallagher: Okay, alright, awesome. Well, thanks so much for your time today, I appreciate it. It was great meeting you.
69 00:09:36.110 ⇒ 00:09:38.330 Indu Gaddam: You too. Alrighty, a good one.
70 00:09:38.330 ⇒ 00:09:39.870 Kaela Gallagher: You too. Bye.