Meeting Title: Brainforge AI Engineer Interview Date: 2026-04-29 Meeting participants: Kaela Gallagher, Cole Carter
WEBVTT
1 00:00:13.160 ⇒ 00:00:14.829 Kaela Gallagher: Hey, Cole, how’s it going?
2 00:00:15.730 ⇒ 00:00:17.110 Cole Carter: Hey, Kayla, can you hear me?
3 00:00:17.560 ⇒ 00:00:20.380 Kaela Gallagher: Yeah, I can hear you just fine. How’s it going?
4 00:00:21.020 ⇒ 00:00:26.100 Cole Carter: I’m doing okay, just got back from travel, and I think I got, like, a sinus infection or something.
5 00:00:26.560 ⇒ 00:00:27.370 Cole Carter: Ugh.
6 00:00:27.660 ⇒ 00:00:30.090 Kaela Gallagher: Yeah, I’m not sure. Oh, bummer.
7 00:00:30.240 ⇒ 00:00:31.360 Cole Carter: Gotta survive.
8 00:00:31.840 ⇒ 00:00:34.019 Cole Carter: all the catch-up work that I have to do, on top.
9 00:00:34.020 ⇒ 00:00:37.580 Kaela Gallagher: So, having a sinus infection, so… Not bad.
10 00:00:37.580 ⇒ 00:00:39.279 Cole Carter: But it is what it is.
11 00:00:39.400 ⇒ 00:00:42.160 Kaela Gallagher: Yeah, where… where did you travel to?
12 00:00:42.830 ⇒ 00:00:44.119 Cole Carter: Went to Puerto Rico.
13 00:00:44.580 ⇒ 00:00:47.799 Kaela Gallagher: Oh my gosh, okay, that’s cool. Was it your first time?
14 00:00:48.460 ⇒ 00:00:49.979 Cole Carter: My third time, no, my.
15 00:00:49.980 ⇒ 00:00:50.650 Kaela Gallagher: Oh, okay.
16 00:00:50.650 ⇒ 00:00:55.409 Cole Carter: My mom lives there, so we got to crash at her place, and go to the beach, and eat seafood.
17 00:00:55.600 ⇒ 00:00:56.910 Kaela Gallagher: Oh, that’s so fun.
18 00:00:56.910 ⇒ 00:00:58.339 Cole Carter: trees, it’s awesome.
19 00:00:58.630 ⇒ 00:01:12.490 Kaela Gallagher: Okay, okay, cool. So, well, thanks for making time for me amongst all the craziness going on right now, I appreciate it. I came across your profile because
20 00:01:12.490 ⇒ 00:01:27.429 Kaela Gallagher: our team is growing. We’re looking, to add a couple more engineers to our team, and our CEO is based in Austin, so, looking specifically in Austin, which is how I came across your profile.
21 00:01:27.430 ⇒ 00:01:37.370 Kaela Gallagher: We’re a fully remote team, we have team across the globe, but, just being able to meet even on occasion in Austin, I think, is super valuable to us, so…
22 00:01:37.540 ⇒ 00:01:54.190 Kaela Gallagher: That’s how we’re searching there right now. But yeah, would love to just get to know you a little bit, and then I can tell you more about Brainforge, too. Also, apologies for the noise in the background, but I’m actually meeting up with some Brainforge people right now. We’re, like, co-working, so I’m in a coffee shop.
23 00:01:54.190 ⇒ 00:01:54.970 Cole Carter: Austin, too?
24 00:01:54.970 ⇒ 00:01:59.379 Kaela Gallagher: I’m in LA. There’s actually, like, 5 of us out here in LA.
25 00:01:59.700 ⇒ 00:02:07.330 Cole Carter: Okay, okay. No, I get it. I’m on a remote team, too, so we have, like, little hubs. You know, some people in Austin, York, West Coast, yeah, I get it.
26 00:02:07.710 ⇒ 00:02:10.360 Kaela Gallagher: Yeah, okay, cool.
27 00:02:10.360 ⇒ 00:02:17.389 Cole Carter: Not me, I’m a… I’m a newly minted AI engineer. Before that, I was a data engineer.
28 00:02:17.700 ⇒ 00:02:18.140 Kaela Gallagher: Okay.
29 00:02:18.280 ⇒ 00:02:27.669 Cole Carter: I got hired at Stacker. First, I was a contractor there, and then I got a job offer out of college to be a data engineer somewhere else.
30 00:02:27.830 ⇒ 00:02:31.929 Cole Carter: And they didn’t want to lose me, so they just matched them and brought me on.
31 00:02:32.930 ⇒ 00:02:38.160 Cole Carter: Stacker itself is, like, a newswire company, kind of like Associated Press, except for.
32 00:02:38.160 ⇒ 00:02:39.380 Kaela Gallagher: Whoa.
33 00:02:39.670 ⇒ 00:02:40.130 Cole Carter: So…
34 00:02:40.130 ⇒ 00:02:40.780 Kaela Gallagher: Okay.
35 00:02:40.780 ⇒ 00:02:42.089 Cole Carter: Bunch of different news.
36 00:02:42.920 ⇒ 00:02:50.010 Cole Carter: Publishers, different articles, and at a pretty rapid rate, there’s, like, thousands of publishers, and…
37 00:02:50.310 ⇒ 00:02:53.199 Cole Carter: They do, I want to say, like, a few hundred stories a month.
38 00:02:54.240 ⇒ 00:02:55.070 Kaela Gallagher: Okay, wow.
39 00:02:55.070 ⇒ 00:03:02.500 Cole Carter: they have this, huge data corpus, and they wanted to do stuff with it, so they brought me on, and since I’ve been on, we’ve built
40 00:03:03.560 ⇒ 00:03:11.679 Cole Carter: a recommendation system for brands to publish stories that do well on the newswire, and now we’re pivoting into…
41 00:03:12.010 ⇒ 00:03:18.490 Cole Carter: building out pipelines and reporting for AI search, since that’s the big craze now. Companies want.
42 00:03:18.490 ⇒ 00:03:19.450 Kaela Gallagher: to show up.
43 00:03:19.450 ⇒ 00:03:25.379 Cole Carter: When people put, like, ChatGPT, what’s the best water bottle? And it says, Yeti is the best.
44 00:03:25.670 ⇒ 00:03:26.750 Kaela Gallagher: Yeti wants that.
45 00:03:26.750 ⇒ 00:03:31.389 Cole Carter: So, trying to prove out that that’s… value that Stacker can drive.
46 00:03:32.670 ⇒ 00:03:34.640 Cole Carter: As for me, specifically…
47 00:03:35.000 ⇒ 00:03:44.699 Cole Carter: I really like machine learning and AI. I kind of spent all my time with it. Even in my free time. I’m building, like, open claw agents and stuff like that.
48 00:03:44.950 ⇒ 00:03:48.310 Cole Carter: To sort of automate some of my life stuff, and just for fun, honestly.
49 00:03:49.150 ⇒ 00:03:53.929 Cole Carter: And I’ve been that way probably for the last decade or so, since…
50 00:03:54.220 ⇒ 00:03:58.840 Cole Carter: the first AI started beating, like, the best chess players, or sorry, the first…
51 00:03:59.280 ⇒ 00:04:07.429 Cole Carter: neural network AIs started beating the best chess AIs of the time, like, a decade ago. Got me, like, hooked. And so, since then, I’ve just been reading…
52 00:04:08.010 ⇒ 00:04:12.190 Cole Carter: Research paper after research paper of… AI helping, whether it’s, like…
53 00:04:12.880 ⇒ 00:04:17.619 Cole Carter: Protein folding, or energy efficiency, or all these different things that are happening.
54 00:04:18.279 ⇒ 00:04:29.339 Kaela Gallagher: Okay, cool. It’s great to hear that you’re… you’re passionate about it, even outside of work. That’s super important to us. We’re always, like, trying to discover the newest things, and…
55 00:04:29.339 ⇒ 00:04:50.209 Kaela Gallagher: we’re not only, you know, client-facing as, like, a consultancy, but especially our AI team is working on internal tooling as well, and, like, our own kind of platform and version of, like, a chat GPT, so, having that passion for it and, like, coming to the table with new ideas is super cool. So love to hear that.
56 00:04:50.209 ⇒ 00:04:51.719 Kaela Gallagher: I’m curious, like.
57 00:04:51.789 ⇒ 00:05:02.489 Kaela Gallagher: at this point, now that you’ve been with Stacker, I think I saw, like, over, a year, or two years, what’s kind of, like, motivating you to look for something new?
58 00:05:03.570 ⇒ 00:05:14.070 Cole Carter: Nothing necessarily, I kind of just am always looking for awesome opportunities, and if you guys have awesome opportunities, then, you know, it’s more of a pull factor than a push factor, I would say.
59 00:05:14.540 ⇒ 00:05:19.009 Kaela Gallagher: Okay, okay, that makes sense. What part of, Austin are you located in?
60 00:05:19.880 ⇒ 00:05:23.700 Cole Carter: West… do you know Far West Boulevard? Or do you know Austin area?
61 00:05:24.620 ⇒ 00:05:30.210 Kaela Gallagher: I just went for the first time last week, but I do know that our CEO lives on the east side.
62 00:05:31.110 ⇒ 00:05:33.260 Cole Carter: Okay. Other set of 35, then.
63 00:05:34.320 ⇒ 00:05:34.640 Kaela Gallagher: Yeah.
64 00:05:35.120 ⇒ 00:05:37.650 Cole Carter: Yeah, but off of Far West Boulevard…
65 00:05:37.930 ⇒ 00:05:42.250 Cole Carter: Thinking about moving further south, but… We’ll see.
66 00:05:42.670 ⇒ 00:05:48.239 Kaela Gallagher: Okay, okay, cool. Have you been in Texas for, like, most of your life?
67 00:05:48.810 ⇒ 00:05:49.570 Cole Carter: Yep, pretty much.
68 00:05:49.570 ⇒ 00:05:49.920 Kaela Gallagher: Okay.
69 00:05:49.920 ⇒ 00:05:53.710 Cole Carter: It’s up, like, one year, but I’ve been in Austin since…
70 00:05:54.040 ⇒ 00:05:56.919 Cole Carter: 2017 or so. Okay. Where I went to school.
71 00:05:57.280 ⇒ 00:06:00.580 Kaela Gallagher: Okay, cool.
72 00:06:00.730 ⇒ 00:06:06.499 Kaela Gallagher: In terms of, like, your next opportunity, curious what kind of pay you would be looking for.
73 00:06:08.260 ⇒ 00:06:12.510 Cole Carter: Yeah. Is the… the role title is AI Engineer, right?
74 00:06:13.210 ⇒ 00:06:22.150 Kaela Gallagher: Yeah, so right now, the two roles we’re looking to fill would be an AI engineer and then an analytics engineer. I’m assuming you’re more interested in the AI one.
75 00:06:22.630 ⇒ 00:06:42.610 Cole Carter: Yeah, I don’t know too much about, like, analytics engineer market, but from what I’ve seen for AI engineer market, typically, like, 130 to 160 with options, or…
76 00:06:42.740 ⇒ 00:06:44.260 Cole Carter: RSUs, or whatever.
77 00:06:44.930 ⇒ 00:07:09.429 Kaela Gallagher: Okay, okay. Just to give, kind of an overview of how we’re structured right now, our entire team’s on a 1099 basis, so independent contractors, which means we don’t have equity in play, so our, our, like, hourly rate is basically going to be a flat rate. That being said, like, we offer bonuses to the entire company for
78 00:07:09.430 ⇒ 00:07:19.450 Kaela Gallagher: Referrals, we offer spot bonuses for, you know, any, like, love letters coming from clients or anything like that, just, like, exceptional work.
79 00:07:19.450 ⇒ 00:07:26.849 Kaela Gallagher: We offer bonuses for obtaining certifications that are relevant to your role, and then we offer,
80 00:07:26.850 ⇒ 00:07:40.840 Kaela Gallagher: a percentage share if you bring in new clients, or if you expand current clients’ scope of work. So, beyond, you know, like, a base rate, there’s still opportunity to earn outside of that.
81 00:07:41.300 ⇒ 00:07:43.619 Cole Carter: Okay, so it’s almost like a…
82 00:07:43.890 ⇒ 00:07:46.550 Cole Carter: a little bit of account management thrown in, I guess.
83 00:07:47.950 ⇒ 00:08:03.220 Kaela Gallagher: In an AI engineer position, that’s not going to be necessarily an expectation, but, like, we do just offer that across the board for anybody who wants to take that on.
84 00:08:04.000 ⇒ 00:08:17.100 Kaela Gallagher: For the AI engineer role, so we’re about 25 people right now, so all of our engineers are still joining client calls, so that, like, communication ability, understanding stakeholders, and obviously, like.
85 00:08:17.100 ⇒ 00:08:28.429 Kaela Gallagher: explaining technical concepts in a way that makes sense to anybody is really important to us. And then you would probably be working on, you know, like, two to three clients at a time, so…
86 00:08:28.430 ⇒ 00:08:33.190 Kaela Gallagher: Being able to context switch between them as well is super important to us.
87 00:08:35.000 ⇒ 00:08:57.750 Kaela Gallagher: And then in terms of the kind of clients that we serve, small to mid-sized organizations, although, some of them are, like, on the shelf at Target and Walmart, so you might recognize them. So a lot of, like, CPG or e-com brands, but then also, like, healthcare and SaaS, so a good, you know, range of industries. I feel like
88 00:08:57.750 ⇒ 00:09:05.390 Kaela Gallagher: You can get 5 years of experience in one year in consulting with the number of clients that you touch, so…
89 00:09:05.390 ⇒ 00:09:06.239 Kaela Gallagher: I mean, I…
90 00:09:06.290 ⇒ 00:09:10.390 Cole Carter: I’m, you know, pretty early career, so any kind of, like, growth
91 00:09:10.530 ⇒ 00:09:15.450 Cole Carter: type of things is usually what I try to optimize for, as far as, like, projects that I like to take on.
92 00:09:15.970 ⇒ 00:09:16.400 Kaela Gallagher: Yeah.
93 00:09:16.400 ⇒ 00:09:18.479 Cole Carter: Oh, that’s cool to hear from y’all’s angle.
94 00:09:18.970 ⇒ 00:09:19.360 Kaela Gallagher: Yeah.
95 00:09:19.360 ⇒ 00:09:20.649 Cole Carter: More on,
96 00:09:20.960 ⇒ 00:09:27.739 Cole Carter: I guess my background at Stacker. I’m on the product team, so I already do a lot of that kind of client-facing stuff.
97 00:09:28.020 ⇒ 00:09:33.019 Cole Carter: You know, sitting in on calls, hearing user stories directly, and then…
98 00:09:33.400 ⇒ 00:09:40.120 Cole Carter: Validating whatever features we come up with, or reporting types, metrics, that those land with clients, you know, visually.
99 00:09:40.120 ⇒ 00:09:40.870 Kaela Gallagher: Excellent.
100 00:09:41.170 ⇒ 00:09:42.650 Cole Carter: Statistically, whatever.
101 00:09:43.110 ⇒ 00:09:47.920 Kaela Gallagher: Yeah. Okay, cool, yeah, that seems super, super relevant.
102 00:09:47.950 ⇒ 00:10:12.929 Kaela Gallagher: Yeah, in terms of, like, what next steps would look like in the process, it would be three rounds. The first one is just kind of an overview of your experience. The second one dives more into the technical side. There’s no, like, live coding or anything, but, just digging into, like, technical concepts. And then the third one, we’d give you a take-home challenge, and you’d bring your solution to a final panel and present
103 00:10:12.930 ⇒ 00:10:15.430 Kaela Gallagher: As if you were presenting to, like, a client.
104 00:10:15.840 ⇒ 00:10:29.360 Kaela Gallagher: So, that’s the setup for each round. We send you a booking link, to schedule it, so the quicker you schedule, the quicker we move through it. But yeah, curious if there’s, like, any questions I can help answer.
105 00:10:30.740 ⇒ 00:10:35.470 Cole Carter: Yeah, I guess just jumping back to the salary range question, if it’s hourly.
106 00:10:35.590 ⇒ 00:10:40.399 Cole Carter: How do you guys calculate that? Is it, like, a strict, this is the salary rate.
107 00:10:40.510 ⇒ 00:10:46.339 Cole Carter: have that to get the hourly, you know, like, 65 an hour kind of deal?
108 00:10:46.830 ⇒ 00:10:50.169 Kaela Gallagher: Yeah, yep, that’s typically how we’d break it down, yeah. Okay.
109 00:10:50.310 ⇒ 00:11:05.139 Kaela Gallagher: And then obviously, like, I don’t know, if you take, like, yeah, 130, have it, and 65, but then if you work 40 hours a week, all 52 weeks of the year, it’ll turn out to be a little bit more than 130, but yeah, I think 65 is, like, a fair estimate, yeah.
110 00:11:05.530 ⇒ 00:11:06.910 Cole Carter: Okay. Cool.
111 00:11:07.380 ⇒ 00:11:10.959 Cole Carter: And then you already answered my question, so I was gonna ask, like, what…
112 00:11:11.220 ⇒ 00:11:15.150 Cole Carter: clients you guys work for. I saw a few case studies on y’all’s website.
113 00:11:15.820 ⇒ 00:11:16.409 Cole Carter: two of them.
114 00:11:16.600 ⇒ 00:11:18.760 Cole Carter: And it’s pretty interesting, but…
115 00:11:19.130 ⇒ 00:11:31.279 Cole Carter: Of the case studies that I saw, I didn’t see a whole lot of actual AI engineering work in there. Maybe those aren’t published in your case studies, or is it something that you’re branching into that you don’t have a lot of representation right now?
116 00:11:31.670 ⇒ 00:11:32.310 Kaela Gallagher: Yeah, so…
117 00:11:32.310 ⇒ 00:11:33.580 Cole Carter: EI type stuff.
118 00:11:33.880 ⇒ 00:11:49.110 Kaela Gallagher: Yeah, a lot of our, AI work is with clients that we’re still currently working with, so what’s listed on our website is, like, former clients. All of the… our current clients, we can’t, like, disclose the names.
119 00:11:50.690 ⇒ 00:11:59.390 Kaela Gallagher: typically how, like, our AI work comes into play, sometimes we can, like, sell it directly and start on an AI project, but I feel like
120 00:11:59.390 ⇒ 00:12:12.590 Kaela Gallagher: more realistically, clients want help with, like, data structure and, like, cleaning up data, and maybe moving things into Snowflake first, and then we end up, bringing in AI work,
121 00:12:12.650 ⇒ 00:12:25.310 Kaela Gallagher: But then our AI team ends up supporting, like, a lot of internal tooling, too, like I mentioned. So we have, like, a huge repository of every call we’ve ever had, and all of our company knowledge, and
122 00:12:25.420 ⇒ 00:12:32.250 Kaela Gallagher: our own kind of platform that we call the Forge, so there’s, like, a lot of work to be done there, too.
123 00:12:32.500 ⇒ 00:12:36.429 Cole Carter: That’s cool, so maybe some snippet from this convo ends up in some Slack chat?
124 00:12:36.650 ⇒ 00:12:55.649 Kaela Gallagher: Maybe, I mean, I can… I can go into this call later, and I can literally, like, we have functions that say, like, oh, create a Slack summary from this, create an email summary, oh, tell me what my action items are from the meeting, or copy the transcript, or anything like that, so…
125 00:12:55.650 ⇒ 00:12:56.970 Kaela Gallagher: Yeah.
126 00:12:56.970 ⇒ 00:13:09.779 Kaela Gallagher: cool functions, especially when you’re doing client work. Like, if somebody joins a client that we’ve had for a while, they can immediately get caught up through Cursor and, like, our repository of knowledge on
127 00:13:09.850 ⇒ 00:13:15.890 Kaela Gallagher: What’s been going on, so… Yeah, really cool features, yeah.
128 00:13:17.040 ⇒ 00:13:19.140 Cole Carter: Cursor… by cursor, do you mean, like, the…
129 00:13:19.260 ⇒ 00:13:22.820 Cole Carter: IDE, the coding environment, or do you mean a different product?
130 00:13:23.140 ⇒ 00:13:34.640 Kaela Gallagher: Yeah, so we’re using Cursor as kind of, like, an internal, like, you know, instead of, like, a Claude or a ChatGBT, we’re using it as, like, an AI tool for us internally.
131 00:13:34.840 ⇒ 00:13:38.419 Cole Carter: Okay. I use, like, Claude Code pretty much exclusively, so…
132 00:13:38.730 ⇒ 00:13:39.150 Kaela Gallagher: Okay.
133 00:13:39.230 ⇒ 00:13:41.110 Cole Carter: I would imagine there’s some overlap, but…
134 00:13:41.820 ⇒ 00:13:58.200 Kaela Gallagher: From what I’ve heard, fairly similar. We also recently tried open code, so I think some of our team is using open code as well, maybe more on the development side, but for me, cursor is as far as I go.
135 00:13:58.200 ⇒ 00:13:59.300 Cole Carter: It’s tough, it’s tough.
136 00:13:59.750 ⇒ 00:14:01.889 Cole Carter: There’s a new thing every month, right, to learn?
137 00:14:01.890 ⇒ 00:14:03.970 Kaela Gallagher: Oh my god. Yes, yeah.
138 00:14:07.380 ⇒ 00:14:08.219 Kaela Gallagher: But that’s all.
139 00:14:09.160 ⇒ 00:14:09.850 Kaela Gallagher: Okay!
140 00:14:09.850 ⇒ 00:14:13.049 Cole Carter: Anything else you need from me? You said you’re gonna send a second…
141 00:14:13.050 ⇒ 00:14:29.010 Kaela Gallagher: Oh, I’ll get… yeah, I’ll get the booking link sent over to you for the first round, and then there is a chance that, given that our CEO was just down the road from you, he might want to meet up for, like, coffee or something sometime soon, so I’ll keep you posted on that, too.
142 00:14:29.790 ⇒ 00:14:38.009 Cole Carter: Cool. And then, just to reiterate the interview process, you said it was, like, round 1, 2, 3. Could you describe those one more time?
143 00:14:38.010 ⇒ 00:14:49.009 Kaela Gallagher: Yes, and I’ll send it over via email, too, what those will be, but it’ll be kind of just, like, a cultural experience bit, a technical, and then, like, a final challenge with a panel.
144 00:14:49.320 ⇒ 00:14:50.570 Kaela Gallagher: Gotcha.
145 00:14:50.570 ⇒ 00:14:51.889 Cole Carter: Okay, that sounds good.
146 00:14:52.390 ⇒ 00:14:55.629 Kaela Gallagher: Awesome! Cole, thanks so much for your time, Nicole, I appreciate it.
147 00:14:55.690 ⇒ 00:14:56.940 Cole Carter: Thanks for reaching out, Caleb.
148 00:14:56.940 ⇒ 00:14:58.749 Kaela Gallagher: Of course, talk to you later.
149 00:14:59.020 ⇒ 00:14:59.790 Cole Carter: See ya.
150 00:14:59.790 ⇒ 00:15:00.579 Kaela Gallagher: Alright, bye.