Meeting Title: Brainforge x Selam Candidate Interview Date: 2026-03-27 Meeting participants: Kaela Gallagher, Selam
WEBVTT
1 00:00:06.350 ⇒ 00:00:08.810 Kaela Gallagher: Hey, good morning. How’s it going?
2 00:00:08.960 ⇒ 00:00:11.240 Selam: Good morning. Doing well, how are you?
3 00:00:11.440 ⇒ 00:00:17.020 Kaela Gallagher: Good! Thanks so much for taking the time to meet with me. Appreciate it.
4 00:00:17.370 ⇒ 00:00:20.349 Kaela Gallagher: It was Chad that put us in touch, right?
5 00:00:20.530 ⇒ 00:00:21.180 Selam: Yes.
6 00:00:21.180 ⇒ 00:00:36.759 Kaela Gallagher: Okay, okay, awesome, cool. Yeah, we recently, connected with him and just asked if he knew of anybody on the market, and he recommended you, so excited to learn a little bit more about your background and,
7 00:00:36.760 ⇒ 00:00:42.000 Kaela Gallagher: Yeah, I guess just starting off, like, curious what’s putting you on the market for a new position?
8 00:00:42.280 ⇒ 00:00:57.999 Selam: Oh yeah, sure. So for about the past year, I’ve been working on building a startup with about 2 other devs. We were in the healthcare space, so we were working on building a startup, EffaCover, where we were looking to reduce the overhead for dentists or dental clinics.
9 00:00:58.000 ⇒ 00:01:04.629 Selam: We were initially starting off just trying to learn about problems for… between, like, medical doctors, insurance workers.
10 00:01:04.629 ⇒ 00:01:16.030 Selam: dentists and dental clinics and front desk staff workers, and when we, like, looked at the survey data and, like, the conversations that we had with these individuals, aside from prior authorizations, which is kind of where we started at first, like.
11 00:01:16.030 ⇒ 00:01:27.160 Selam: essentially, like, the paperwork around that, and I mean, I can go into that, but focusing on this, it was, dealing with the overhead and, like, the repetitive task around dealing with insurance,
12 00:01:27.390 ⇒ 00:01:27.810 Kaela Gallagher: Okay.
13 00:01:27.810 ⇒ 00:01:31.740 Selam: For dental clinics, and dental clinics and dentists that kind of…
14 00:01:31.790 ⇒ 00:01:48.410 Selam: those individuals tend to be kind of underserved in terms of software solutions. It’s very primarily focused on medical doctors, hospitals, and that kind of area. So, what we were trying to do is trying to come up with software solutions for
15 00:01:48.410 ⇒ 00:01:55.979 Selam: How to, get… collect insurance, verify individual softwares, because there’s a lot of, kind of, segmented solutions.
16 00:01:55.980 ⇒ 00:02:02.759 Selam: But, like, a one place that could do that in the background, as well as coming up with a way to deal with, estimation of
17 00:02:05.150 ⇒ 00:02:18.500 Selam: Oh my gosh, estimation of, breakdowns. So, when an individual comes in, they get, like, a better prediction of, like, what of their treatment and, like, the cost associated with that.
18 00:02:18.500 ⇒ 00:02:18.960 Kaela Gallagher: Mmm.
19 00:02:18.960 ⇒ 00:02:19.560 Selam: Good.
20 00:02:20.330 ⇒ 00:02:25.539 Kaela Gallagher: Okay, okay, awesome. So you’ve been working on that, and what’s kind of putting you on the market now?
21 00:02:26.000 ⇒ 00:02:33.550 Selam: So, we got to the point where we had a licensing… we were… had a licensing agreement with another startup, in, like, the East Coast.
22 00:02:33.580 ⇒ 00:02:46.540 Selam: However, like, the amount that they were kind of offering us wasn’t very much between three devs, so it was… I know they were asking for multi-year, so… although it’s an important solution, and we were interested in
23 00:02:46.540 ⇒ 00:02:57.209 Selam: potentially, we’re trying to get something that could help us go for multiple years. It’s just not something that they can meet us at, so right now, even though it’s an important problem and
24 00:02:57.210 ⇒ 00:03:07.389 Selam: something that we’re still, like, interested in and passionate about. It’s just not something that we can do, so that’s why I’m just looking for something else and not really interested in pursuing that path.
25 00:03:07.780 ⇒ 00:03:15.989 Kaela Gallagher: Okay, okay, got it. And what kind of roles have you been looking into so far? Like, data engineering positions, or what kind of roles?
26 00:03:16.140 ⇒ 00:03:29.129 Selam: Software and AI engineer, I’ve just kind of looked at the market now, I’ve seen way more AI engineering roles, which is why I reached out. I saw… I saw he posted about a different role, but I saw that you had an AI engineering role, so that’s why I asked about this.
27 00:03:29.400 ⇒ 00:03:33.930 Kaela Gallagher: Okay, okay, got it. What’s your experience with AI engineering?
28 00:03:34.670 ⇒ 00:03:40.470 Selam: I had the opportunity to work a little bit with,
29 00:03:40.580 ⇒ 00:03:59.169 Selam: like, mostly as a dev where I’ve integrated, like… at Redfin, we had a data science team that worked a lot more with TensorFlow, so I worked on, like, integrating their solutions into, like, creating APIs to make their solutions, like, available to other software engineers.
30 00:03:59.170 ⇒ 00:04:13.019 Selam: I’ve also, kind of, what I’ve been doing at my startup for the past year, we’re very AI-forward, so working with Cursor, developing, like, the prompts, the services that we had are all
31 00:04:13.070 ⇒ 00:04:19.440 Selam: AI-focused, so I… I would consider that, like, a majority of the experience that I’ve had, so…
32 00:04:20.260 ⇒ 00:04:20.760 Kaela Gallagher: Okay.
33 00:04:20.769 ⇒ 00:04:24.759 Selam: Where I’ve gotten my ex… a majority of my exposure.
34 00:04:25.090 ⇒ 00:04:31.219 Kaela Gallagher: Okay, okay, cool. And where… where are you currently based?
35 00:04:31.630 ⇒ 00:04:32.400 Selam: Seattle.
36 00:04:32.620 ⇒ 00:04:39.359 Kaela Gallagher: Okay, got it. Are you open to, like, relocation in the future, or looking to stay in the Seattle area?
37 00:04:39.690 ⇒ 00:04:41.470 Selam: I’m looking to stay in Seattle.
38 00:04:41.470 ⇒ 00:04:52.069 Kaela Gallagher: Okay, okay. We are a fully remote organization currently. We have talent actually across the globe, although we’re all working, like, US time zones.
39 00:04:52.290 ⇒ 00:05:11.849 Kaela Gallagher: the reason I ask about relocation is because we’ve actually started to hire quite a few people in, like, the LA and Austin areas. So not, like, a requirement for people to be there by any means, but definitely, like, a bonus because we just get together and see each other and co-work on occasion, so that’s why I ask.
40 00:05:13.360 ⇒ 00:05:19.339 Kaela Gallagher: Okay, cool, and then in terms of, like, the compensation range that you’re targeting, what are you looking at currently?
41 00:05:20.100 ⇒ 00:05:34.089 Selam: It depends, there are things that make me, like, would probably change how I feel about compensation, so… probably want to know about, like, what on-call looks like, that kind of sort… that kind of stuff, so… is there a range that you had in mind?
42 00:05:34.650 ⇒ 00:05:51.960 Kaela Gallagher: Yeah, so for our compensation ranges, I will say we actually just recently extended an offer for the AI, engineer position. So, our, like, kind of hot openings currently would be our data engineer role and our analytics engineer role.
43 00:05:51.960 ⇒ 00:05:54.979 Kaela Gallagher: The compensation for those varies.
44 00:05:55.000 ⇒ 00:06:12.940 Kaela Gallagher: Based on, like, level of seniority, but, we have everybody on a 1099 contracting basis right now, so do just want to call out that it would be, like, an independent contracting agreement, and paid out, like, on an hourly basis. Is that something that you’re comfortable with?
45 00:06:14.670 ⇒ 00:06:18.279 Selam: Yeah, as long as it was, like, in a…
46 00:06:18.420 ⇒ 00:06:22.040 Selam: in an appropriate range, I would be open to that.
47 00:06:22.250 ⇒ 00:06:34.349 Kaela Gallagher: Okay, okay, cool. Yeah, I mean, depending on seniority, I would say we’re looking at, like, 120 to 180 annually. Is that, something that you’re open to?
48 00:06:35.520 ⇒ 00:06:48.330 Kaela Gallagher: Okay, okay, got it. What’s kind of feel like your… your baseline, I guess, considering it would be, like, 1099 hourly, and at least initially there wouldn’t be benefits offered?
49 00:06:49.710 ⇒ 00:06:51.150 Selam: My baseline for salary?
50 00:06:51.150 ⇒ 00:06:54.659 Kaela Gallagher: Yes, yeah, for, like, compensation, like, what you’d be targeting.
51 00:06:55.890 ⇒ 00:07:01.880 Selam: Oh, within the… within the range. I think the more that I learn about the role, then I would be able to give you more of an idea.
52 00:07:01.880 ⇒ 00:07:18.869 Kaela Gallagher: Okay, sounds good. Just to give, like, a little bit more insight to Brainforge and kind of what we do, we’re a data and AI consulting organization, so we work with various clients, mostly, like, small to mid-sized organizations across different industries.
53 00:07:18.870 ⇒ 00:07:26.620 Kaela Gallagher: we work with quite a few, like, CPG brands that you’d actually find in, like, Target and Walmart. I think you’d recognize the names.
54 00:07:26.670 ⇒ 00:07:41.239 Kaela Gallagher: like, healthcare, financial, B2B, SaaS, different kinds of companies. Our average engagement is typically just a few months, but we do have clients that we’ve worked with for over a year, and we serve as more of, like, an in-house
55 00:07:41.240 ⇒ 00:07:51.519 Kaela Gallagher: team to them, so kind of depends on the client, but as a data or analytics engineer, you would likely be supporting, like, 2 to 3 clients at a time.
56 00:07:51.720 ⇒ 00:07:56.889 Kaela Gallagher: So, that’s kind of the overview there. Any questions that I could help answer?
57 00:07:57.190 ⇒ 00:08:03.970 Selam: Just to clarify, so the AI and analytics role, the AI and automation engineer role you said was already filled, so…
58 00:08:04.130 ⇒ 00:08:08.839 Selam: You’re looking for just a data or analytics position to be filled?
59 00:08:09.040 ⇒ 00:08:19.530 Kaela Gallagher: Correct, yes. We do see ourselves, like, hiring another AI position, probably in the next, like, few months, but we did just fill our opening.
60 00:08:20.080 ⇒ 00:08:20.860 Selam: Okay.
61 00:08:21.180 ⇒ 00:08:32.849 Kaela Gallagher: Yeah. Would you still be interested in, like, moving forward with the data or analytics role, or would you prefer that I, like, reach out in a few months, reconnect for something, like, more AI-focused?
62 00:08:33.370 ⇒ 00:08:40.780 Selam: No, I’m open to those, I just… I didn’t look at the rec, so, just as a heads up, I… about the level of context.
63 00:08:41.140 ⇒ 00:08:44.650 Kaela Gallagher: Okay, yeah, no worries at all.
64 00:08:45.040 ⇒ 00:09:02.540 Kaela Gallagher: Yeah, our data and analytics engineering positions both fall within our data team. We work a lot with, like, dbt, Snowflake, as a BI tool. Omni is probably our biggest one, although we’re, like, flexible with, you know, what our clients have in place.
65 00:09:02.710 ⇒ 00:09:18.800 Kaela Gallagher: A lot of our engineers have, like, a Python or a TypeScript background, so that’s just kind of an overview there, but given that we’re, like, working with different clients, we don’t have, like, a very, defined, like, tech stack per se.
66 00:09:20.020 ⇒ 00:09:20.730 Selam: Okay.
67 00:09:21.240 ⇒ 00:09:23.169 Kaela Gallagher: Yeah.
68 00:09:23.910 ⇒ 00:09:38.730 Kaela Gallagher: In terms of the interview process, what it would look like is it’s three rounds. The first one is more so about your experience, maybe a couple technical concepts, but then the second one dives in a little bit deeper into your technical experience.
69 00:09:38.730 ⇒ 00:09:44.740 Kaela Gallagher: No live coding or anything like that. And then the final round is a take-home challenge.
70 00:09:45.090 ⇒ 00:09:55.929 Kaela Gallagher: So we’ll send you the challenge ahead of time, and then you bring your solution and your code to the final panel. So that’s kind of how we structure it. Any questions I can help answer about that?
71 00:09:57.220 ⇒ 00:09:58.230 Selam: No.
72 00:09:58.440 ⇒ 00:10:04.310 Kaela Gallagher: Okay. Okay. Any other questions for me about Brainforge? Anything I can help answer?
73 00:10:05.260 ⇒ 00:10:09.330 Selam: I’m curious how you use AI at, Brainforge.
74 00:10:10.100 ⇒ 00:10:20.370 Kaela Gallagher: Yeah, so we have, an internal platform. So, I mean, I’m recruiting in people, so I’m using AI,
75 00:10:20.680 ⇒ 00:10:31.219 Kaela Gallagher: in, like, my daily life, whether that’s, like, helping brainstorm job descriptions or, you know, programs that I can implement across the company.
76 00:10:32.760 ⇒ 00:10:46.579 Kaela Gallagher: we use Cursor as our internal tool, and it’s connected to basically, like, our brain of the company, and all of our resources. I can also, like, go into a call with a team member and ask Cursor for context on them.
77 00:10:46.580 ⇒ 00:10:53.730 Kaela Gallagher: It’s a really, really cool feature, but obviously our technical team is using it much more than I am.
78 00:10:54.960 ⇒ 00:10:56.449 Selam: Okay, cool. Thank you.
79 00:10:56.910 ⇒ 00:10:58.200 Kaela Gallagher: Yeah, of course.
80 00:10:58.500 ⇒ 00:11:00.610 Kaela Gallagher: Cool.
81 00:11:00.920 ⇒ 00:11:14.999 Kaela Gallagher: I… I don’t think I have any other questions for you, but I can get back to you in the next couple days with some feedback, and next steps. Anything that you… you need from me?
82 00:11:19.270 ⇒ 00:11:19.960 Kaela Gallagher: Okay.
83 00:11:20.100 ⇒ 00:11:28.059 Kaela Gallagher: Alrighty, cool. Well, thanks so much for your time. I’m glad that Chad was able to connect us. It was great getting to know you, and yeah, we’ll chat again soon.
84 00:11:28.280 ⇒ 00:11:29.449 Selam: Okay, thank you.
85 00:11:29.450 ⇒ 00:11:31.280 Kaela Gallagher: Bye. Thanks. Bye.