Meeting Title: Brainforge AI Engineer Interview Date: 2026-04-09 Meeting participants: 220995 Touseef Hanif, Kaela Gallagher
WEBVTT
1 00:00:19.360 ⇒ 00:00:20.730 Kaela Gallagher: Good morning!
2 00:00:23.080 ⇒ 00:00:23.890 Kaela Gallagher: Hello?
3 00:00:24.220 ⇒ 00:00:25.400 Kaela Gallagher: Good evening, Harry.
4 00:00:25.580 ⇒ 00:00:26.400 Kaela Gallagher: It’s not bad.
5 00:00:27.910 ⇒ 00:00:29.250 Kaela Gallagher: Can you hear me okay?
6 00:00:29.820 ⇒ 00:00:31.180 Kaela Gallagher: Oh, yes, I can hear you.
7 00:00:33.910 ⇒ 00:00:38.679 Kaela Gallagher: I’m having some trouble… Hearing you, it’s, like, very quiet.
8 00:00:47.550 ⇒ 00:00:48.850 220995 Touseef Hanif: No, please judge me.
9 00:00:50.390 ⇒ 00:00:51.260 220995 Touseef Hanif: That’s okay.
10 00:00:52.560 ⇒ 00:00:57.550 Kaela Gallagher: Hmm… I wonder what’s going on… I’m also…
11 00:00:57.830 ⇒ 00:01:00.440 Kaela Gallagher: I also can’t see you, either.
12 00:01:05.300 ⇒ 00:01:08.010 Kaela Gallagher: Okay, now the video’s coming through, but…
13 00:01:11.540 ⇒ 00:01:15.879 Kaela Gallagher: There is, like, some audio, but it’s just super, super quiet.
14 00:01:26.480 ⇒ 00:01:30.080 220995 Touseef Hanif: I think there is alright there, I don’t know why.
15 00:01:30.680 ⇒ 00:01:31.400 220995 Touseef Hanif: For sure.
16 00:01:36.240 ⇒ 00:01:38.969 Kaela Gallagher: Do you… are you using, like, a headphone or something?
17 00:01:39.300 ⇒ 00:01:39.980 220995 Touseef Hanif: Yes.
18 00:01:40.170 ⇒ 00:01:41.580 220995 Touseef Hanif: I’m really hopeful.
19 00:01:42.110 ⇒ 00:01:44.610 Kaela Gallagher: Oh… Hmm.
20 00:01:45.890 ⇒ 00:01:48.259 Kaela Gallagher: Maybe it’s the microphone on those.
21 00:01:49.330 ⇒ 00:01:50.050 Kaela Gallagher: Yep.
22 00:01:50.260 ⇒ 00:01:51.309 Kaela Gallagher: Just give me a reason.
23 00:01:55.900 ⇒ 00:01:57.570 220995 Touseef Hanif: No.
24 00:01:58.400 ⇒ 00:02:00.239 Kaela Gallagher: Yes, no, it’s perfect, okay.
25 00:02:00.240 ⇒ 00:02:01.350 220995 Touseef Hanif: Mmm, right.
26 00:02:02.250 ⇒ 00:02:21.169 Kaela Gallagher: Thank you! Awesome! Well, thanks for… yeah, thanks for taking some time to meet with me, I appreciate it. Yeah, just excited to learn a little bit more about you. I think you had, like, shown some interest maybe in a post that we did recently, so, just wanted to reach out and…
27 00:02:21.290 ⇒ 00:02:30.969 Kaela Gallagher: Yeah, I guess just starting off, like, to learn a little bit more about you, what is making you interested in pursuing a new position?
28 00:02:32.200 ⇒ 00:02:42.469 220995 Touseef Hanif: Okay, so, first of all, thank you for having me today with you, and it’s a very interesting opportunity to work with you at Brainforge.
29 00:02:42.470 ⇒ 00:02:53.160 220995 Touseef Hanif: And I learned about this opportunity at LinkedIn, and then I, started to look, what’s your company doing, what’s your services, and then I…
30 00:02:53.470 ⇒ 00:03:06.360 220995 Touseef Hanif: Because the AI and data science roles, I have worked for, for the last two years in the field of AI and data science, where I, contribute to the AI projects.
31 00:03:06.360 ⇒ 00:03:24.809 220995 Touseef Hanif: I’m currently working as an AI engineer at a startup in Pakistan. So, where I build something, a solution to help clients and companies. So, that’s why this role helped… this role helped me to, you know, grow professionally. So, that’s why I, you know.
32 00:03:25.170 ⇒ 00:03:29.999 220995 Touseef Hanif: came across your post and then applied for AI Engineering and Data Science roles.
33 00:03:31.110 ⇒ 00:03:38.870 Kaela Gallagher: Okay, okay, cool. The startup that you’re working for right now, it’s, like, Synca AI?
34 00:03:38.870 ⇒ 00:03:39.850 220995 Touseef Hanif: Yes.
35 00:03:40.040 ⇒ 00:03:43.340 Kaela Gallagher: What, like, do you guys build?
36 00:03:43.950 ⇒ 00:03:54.450 220995 Touseef Hanif: Okay, so basically, it’s a legal AI system for Named, Labot, which is basically helps the lawyer
37 00:03:54.480 ⇒ 00:04:04.110 220995 Touseef Hanif: in Pakistan. We got a dataset from the, laws of Pakistan, then we fine-tuned our Gemini models.
38 00:04:04.290 ⇒ 00:04:14.119 220995 Touseef Hanif: And then we, basically fine-tuned for our specific use cases, and then we started to build something real that helps
39 00:04:14.120 ⇒ 00:04:30.080 220995 Touseef Hanif: our lawyers in Pakistan, so rather than going for each case is, finding it difficult. So this platform helps to, find things quickly, and summarizing things, and summarizing crime cases, and all that.
40 00:04:30.560 ⇒ 00:04:36.499 Kaela Gallagher: Mmm, okay, got it. And what is your role there? Like, what’s your responsibilities?
41 00:04:36.500 ⇒ 00:04:48.160 220995 Touseef Hanif: Okay, so basically, I was working with the AI team, where I, use rack techniques to build that system, or retrieval augmented generation, basically.
42 00:04:48.160 ⇒ 00:05:04.970 220995 Touseef Hanif: Which… in which we make pipelines through the dataset and clean dataset, pre-processing, using some… use some analytics, basically, to find the pattern in the dataset, with the help of some data science techniques and all that.
43 00:05:05.570 ⇒ 00:05:06.410 Kaela Gallagher: Okay.
44 00:05:06.410 ⇒ 00:05:07.310 220995 Touseef Hanif: Okay.
45 00:05:07.390 ⇒ 00:05:23.880 Kaela Gallagher: Cool. I’m curious in that position, or maybe in, like, a previous role, if you have ever, interacted, like, directly with clients, like, met with clients and stakeholders,
46 00:05:24.490 ⇒ 00:05:26.979 Kaela Gallagher: Yeah, curious if you have that experience.
47 00:05:27.010 ⇒ 00:05:33.290 220995 Touseef Hanif: Okay, so, I think you are talking about my summer freelance project, if I’m not wrong.
48 00:05:33.700 ⇒ 00:05:40.199 220995 Touseef Hanif: Yes. Okay, so, in this role, basically, first, I,
49 00:05:40.650 ⇒ 00:05:55.750 220995 Touseef Hanif: basically, it was some PhD professionals who want to research in the field something, computer vision. So, they have a problem to identify the plant ID detection system.
50 00:05:55.750 ⇒ 00:06:06.040 220995 Touseef Hanif: So, I got a research from that, and then, with the help of computer vision techniques, I reserved for them, I drained, open source models, and then…
51 00:06:06.220 ⇒ 00:06:10.130 220995 Touseef Hanif: I head over to there, so there was a research project.
52 00:06:11.680 ⇒ 00:06:12.150 220995 Touseef Hanif: I assume.
53 00:06:12.150 ⇒ 00:06:18.910 Kaela Gallagher: Do you have experience working with international teams? Like, have you ever worked with teams outside of Pakistan?
54 00:06:19.320 ⇒ 00:06:36.510 220995 Touseef Hanif: Okay, so I have a few projects with the international clients, and they are all about the, the consultancy part of the… let’s say, at Sync AI, we have, international clients other than Pakistan, so we,
55 00:06:36.690 ⇒ 00:07:00.099 220995 Touseef Hanif: we interact with the international clients, basically in which we… I consult about, if they come up with the problem, and in… identify the pattern, like, you should do this instead of this, because clients have, very less knowledge about the technical, point, even they have a problem, so I, you know, requirements engineering, I…
56 00:07:00.100 ⇒ 00:07:03.360 220995 Touseef Hanif: I do some engineering stuff, requirement, getting…
57 00:07:03.360 ⇒ 00:07:12.650 220995 Touseef Hanif: From the clients, and then all the process, analysis of that, and then they have a clear mindset of that, actually. So, yeah.
58 00:07:13.410 ⇒ 00:07:22.009 Kaela Gallagher: Okay, okay, great. In terms of compensation expectations, what are you looking for in your next role?
59 00:07:22.700 ⇒ 00:07:42.650 220995 Touseef Hanif: Okay, so, as in Paisan, so it has basically… if I talk about in US dollars, and so, it would be around, like, I’m open and flexible because I want to grow professionally. So, as per the company structure, role, and responsibility.
60 00:07:43.610 ⇒ 00:08:04.600 Kaela Gallagher: Okay, okay. And then, just to tell you, like, a little bit about Brainforge, we’re hiring for an AI engineer position currently, looking for somebody fairly senior that’s interacted with clients before, has strong communication, and because we’re consulting, somebody that can context switch easily between different projects is important.
61 00:08:05.800 ⇒ 00:08:14.599 Kaela Gallagher: We do work US time zones, so even though we’re fully remote, and we even have, another team member in Pakistan.
62 00:08:14.790 ⇒ 00:08:22.009 Kaela Gallagher: we do ask that you work a U.S.-like time zone, so just wanted to make sure that that’s okay with you as well.
63 00:08:22.290 ⇒ 00:08:33.549 220995 Touseef Hanif: Yeah, it’s okay. Basically, at, you are at, in Pakistan now, it’s, like, 9, 8 PM, and at, USI, you just said good morning to me, so that’s
64 00:08:34.140 ⇒ 00:08:51.959 220995 Touseef Hanif: That’s fair, yeah. So, it’s okay for me because, in Pakistan, the whole of the population who are in the tech or software industry, they work at night. So, it’s okay for me to, you know, work for your company and at night all the time.
65 00:08:52.640 ⇒ 00:08:59.649 Kaela Gallagher: Okay, okay, awesome. Are there any questions that you have for me that I can help answer about Brainforge?
66 00:09:00.600 ⇒ 00:09:05.540 220995 Touseef Hanif: Yes, I want to know a bit about the work environment, and…
67 00:09:05.670 ⇒ 00:09:09.259 220995 Touseef Hanif: the role, that I’ve applied for…
68 00:09:10.940 ⇒ 00:09:28.369 Kaela Gallagher: Okay, yeah, so in terms of our work environment, we are fully remote, and we have a global team, so we’re doing a lot of work asynchronously, but at the same time, I think we have a really, like, supportive culture. People are always willing to step in and help out.
69 00:09:28.830 ⇒ 00:09:41.090 Kaela Gallagher: This role would sit within our AI team, and so we have an AI service leader that, you know, holds office hours and is, just great in, like, guiding the direction of this team.
70 00:09:42.800 ⇒ 00:09:43.280 220995 Touseef Hanif: Yes.
71 00:09:43.280 ⇒ 00:10:05.970 Kaela Gallagher: Yeah, we have, like, bi-weekly all-company meetings, so we’re able to interact with, each other quite a bit. And yeah, in terms of this position, I kind of gave an overview of, like, the most important things that we’re looking for. Ai is super new, so hard for us to,
72 00:10:06.140 ⇒ 00:10:10.610 Kaela Gallagher: You know, give, like, a very,
73 00:10:10.750 ⇒ 00:10:27.699 Kaela Gallagher: like, succinct or direct, like, list of technologies that we need in terms of a background, but I will say, our AI engineers all come from a background of either, like, Python or TypeScript, so that’s kind of what’s mostly on our team now.
74 00:10:28.410 ⇒ 00:10:38.430 220995 Touseef Hanif: Okay, so basically, if I talk about my background, actually, I started my journey, 3 years ago, with the web, development, if you are familiar with
75 00:10:38.460 ⇒ 00:11:03.459 220995 Touseef Hanif: So, then I switched to AI because, you know, AI is booming right now. Everyone is using AI tool to assist their work, even HR. And here, one thing I… I want to mention about my final year project in my bachelor’s. Basically, that is related to the AI hiring systems, because sometimes it, contains biasness in fair interior
76 00:11:03.460 ⇒ 00:11:23.889 220995 Touseef Hanif: and take a long process to, you know, let’s say in this role, you review my resume, you review other candidate resume, it will take a lot of time to get or shortlist a person that is relevant to job. So, basically, our system that we are building is doing the same thing.
77 00:11:24.040 ⇒ 00:11:26.809 220995 Touseef Hanif: It basically,
78 00:11:26.810 ⇒ 00:11:46.399 220995 Touseef Hanif: doing less work, let’s say you get a thousand offers, and then our AI system analyzed that, and then we have, interviews, that interviews with… that will check your, technical and behavior, and then we, got a person that is better fit for the job.
79 00:11:47.520 ⇒ 00:11:54.190 Kaela Gallagher: Okay, okay, awesome. Yeah, any other questions that I can help answer?
80 00:11:54.820 ⇒ 00:12:06.239 220995 Touseef Hanif: Oh, yes, when you will, like, shortlist the person for this job, and, what about my background? Is it fit for this job, or, like, what…
81 00:12:08.380 ⇒ 00:12:12.240 Kaela Gallagher: Sorry, you said what about your background as a fit for this role?
82 00:12:12.680 ⇒ 00:12:14.740 220995 Touseef Hanif: Like I’m saying,
83 00:12:14.740 ⇒ 00:12:34.319 220995 Touseef Hanif: You are looking for a person that is fit for your culture and the job that you are… the job person that you are looking for, actually. So, what about my background? So, should I enhance my things, like, in next to two weeks, or when can I join you, and other things?
84 00:12:35.250 ⇒ 00:13:00.040 Kaela Gallagher: Oh, got it. Yeah, our interview process typically takes a couple weeks. What I’ll do is, I’m chatting with quite a few candidates and reviewing a lot of resumes, and I have a team of engineers that’s helping me look at these as well, so I’ll review this conversation in your profile with the team, along with a bunch of other candidates, and then we’ll make a decision on who to move forward to the interview process.
85 00:13:00.250 ⇒ 00:13:05.419 Kaela Gallagher: So, I’ll send you an email if we decide to move forward.
86 00:13:06.030 ⇒ 00:13:08.429 220995 Touseef Hanif: Okay, okay, I got you. Okay.
87 00:13:08.850 ⇒ 00:13:19.859 Kaela Gallagher: Cool. Yeah, I’ll, be following up shortly, hopefully this week, but maybe next, with next steps here, and then if you have any questions at all, just let me know.
88 00:13:21.140 ⇒ 00:13:30.529 220995 Touseef Hanif: Okay, so if I have any question, I’ll directly, text you on a, DM you on LinkedIn, or through email, so…
89 00:13:30.530 ⇒ 00:13:30.980 Kaela Gallagher: Yes.
90 00:13:30.980 ⇒ 00:13:41.560 220995 Touseef Hanif: related, yes, through related to, job, and if, due to certain condition, I got, you…
91 00:13:41.560 ⇒ 00:13:53.710 220995 Touseef Hanif: you will not select me for this job, and I will, certainly join Brentford, because the vision, the team you have, and as you said, and the,
92 00:13:53.740 ⇒ 00:14:03.030 220995 Touseef Hanif: the data science and my interest, and my future research, if I go for PhD or something related to that, that basically fit, for that.
93 00:14:03.890 ⇒ 00:14:10.599 Kaela Gallagher: Okay, okay, perfect. Awesome. Well, thanks so much for your time today. It was great getting to know you, and hope you have.
94 00:14:10.600 ⇒ 00:14:13.110 220995 Touseef Hanif: Thank you, and thank you for your time, basically.
95 00:14:13.620 ⇒ 00:14:15.769 Kaela Gallagher: Yeah, of course. Talk to you later.
96 00:14:16.020 ⇒ 00:14:16.830 220995 Touseef Hanif: Okay.
97 00:14:16.830 ⇒ 00:14:17.760 Kaela Gallagher: Okay, bye.