Meeting Title: Brainforge AI Engineer Interview Date: 2026-03-13 Meeting participants: Dan Hartley, Kaela Gallagher
WEBVTT
1 00:03:36.050 ⇒ 00:03:37.020 Dan Hartley: Hey, Kayla!
2 00:03:37.020 ⇒ 00:03:38.559 Kaela Gallagher: And how’s it going?
3 00:03:38.560 ⇒ 00:03:40.760 Dan Hartley: It’s doing great! How are you?
4 00:03:40.940 ⇒ 00:03:57.890 Kaela Gallagher: Good! Thanks for, for, reaching out and, yeah, taking some time. Excited to get to know a little bit more about you. I guess just first off, wanted to ask, like, how you found about Brainforge and about our openings.
5 00:03:58.150 ⇒ 00:04:10.860 Dan Hartley: Definitely, so, I’m just, like, really active on my job search, and it was just, like, I just, like, go through each and everything. So, yeah, I’m, like, I just, like, was looking up, looking out towards your
6 00:04:10.860 ⇒ 00:04:23.500 Dan Hartley: website, and I saw just, like, a lot of stuff going there, so just, like, went over it, then I searched it out over Google, and just, like, found out about just, like, some… I could just, like, get a personnel to just, like, contact, and that is how, just, like, I reached out.
7 00:04:24.000 ⇒ 00:04:28.850 Kaela Gallagher: Okay, okay, got it. And what is, like, putting you actively on the search?
8 00:04:29.410 ⇒ 00:04:48.250 Dan Hartley: Right. So, what’s putting me actively on my search? And that depends on… like, so let me give you a brief introduction, and then I can answer your question. So, I started off as a software engineer at Redshift, and then I transitioned myself towards being a machine learning engineer.
9 00:04:48.250 ⇒ 00:05:06.480 Dan Hartley: started off being as a machine learning engineer at Goji, and then I transitioned to being a team lead as a senior, working as a senior machine learning engineer at HatchWorks. So when I joined HatchWorks, it was basically, I was one of the foundational engineers over there. Obviously, you know, when you’re joining a small, compact unit, you gotta wear multiple hats at the same time.
10 00:05:06.480 ⇒ 00:05:24.989 Dan Hartley: So, there was a time I was handling… like, machine learning, deep learning, and even just, like, going on handling the backend, and even the cloud deployments and stuff. And then we scaled, so I was just, like, I… and I’m pretty communicative, so I just, like, used to hop onto client meetings, communicate with them, and… because they were service-first, so…
11 00:05:25.000 ⇒ 00:05:47.160 Dan Hartley: I used to gather all the client requirements, convert those into technical feasibilities, and then take it back, and then do back and forth, and then do the development and the lead development right from there. Then it scaled up, and currently I am leading a team of 8-plus engineers. What makes me, active, on my job search is the reason because I feel like I’ve reached the technical ceiling, because
12 00:05:47.160 ⇒ 00:05:56.439 Dan Hartley: Obviously, there are so many engineers that are… unlike almost all of the projects that are currently working, they’re in the maintenance space, there’s, like, a lot of repetitive work that’s hopping in.
13 00:05:56.440 ⇒ 00:06:20.649 Dan Hartley: And if there are a new feature that hops in, so the engineers, they get a little… they get really excited, but obviously, I respect them, that obviously they want to grow, and they want to work in themselves, and they want to just, like, thrive to work. So what I try to do is just, like, assign those tickets to them, because they’ll be like, hey, I want to take on this ticket. I’m like, I think it’s great, it’s a new skill that I would learn. So, like, okay, fine, yeah, okay, you can take it, no worries at all. So it’s majorly in management, and a little bit of hands-on, because I’m mentoring them, and
14 00:06:20.650 ⇒ 00:06:25.469 Dan Hartley: when there’s something going wrong, so I’m looking onto their PRs. So I feel like,
15 00:06:25.470 ⇒ 00:06:47.610 Dan Hartley: Yeah, I’ve pretty much reached where I… just, like, technically, I’ve reached where I wanted to be, and then I’ve just, like, I loved how I built it out, so being, you know, being a foundational engineer, and then scaling it up to a team of 8-plus engineers, and then, so, I feel like, okay, now’s the right time to just, like, go back, relive the experience again, join another firm, scale with them, and then, yeah, that’s one of the reasons.
16 00:06:48.400 ⇒ 00:06:50.870 Kaela Gallagher: Okay. Okay, got it. And…
17 00:06:51.370 ⇒ 00:06:59.810 Kaela Gallagher: Hatchworks, I guess, like, how big was the company when… when you joined, and I guess, what kind of company is it? Like, what kind of service?
18 00:06:59.810 ⇒ 00:07:15.330 Dan Hartley: It is an IT service provider company, so when I joined them, they had, like, multiple modules and multiple… they had, they had, like, a client base. They used to hop in if there’s, like, an owner who’s looking to… they were majorly startup owners, or somewhat, like, product PCs.
19 00:07:15.330 ⇒ 00:07:29.260 Dan Hartley: Some of them were looking for their product maintainances, some of them were looking for new features for their specific products. For startups, they were those, like, personnels who were just… who were just, like, looking out to build something out big.
20 00:07:29.360 ⇒ 00:07:38.089 Dan Hartley: And then take it from there. In terms of how many sites, when I joined them, I believe we were, in total, I think it was anywhere around 12?
21 00:07:38.370 ⇒ 00:07:45.410 Dan Hartley: 2.15, it was all remote. And then, currently, we’re, I think, anywhere around 35.
22 00:07:46.180 ⇒ 00:07:52.279 Kaela Gallagher: Okay, okay, got it. Yeah, that’s kind of similar to us,
23 00:07:52.510 ⇒ 00:08:07.320 Kaela Gallagher: We are about 25 right now, but we’re… we’re growing pretty quickly. We’re looking to add, I would say, like, 4 people in the next few weeks, so, yeah. Hence… hence why we’re hiring an AI engineer.
24 00:08:07.320 ⇒ 00:08:20.870 Kaela Gallagher: I noticed that you had, like, submitted an application, so I do have your profile in front of me, but for some reason, your LinkedIn isn’t working. I’m curious if it was, like, deleted or something.
25 00:08:21.100 ⇒ 00:08:28.999 Dan Hartley: the chore, because I am super… oh, okay, so I am super non-active when it comes to LinkedIn,
26 00:08:29.040 ⇒ 00:08:48.599 Dan Hartley: consider it something like a software development thing, so I did put a link out there, let me check if it’s not still working or not. Okay. But if it’s not, I can provide you my LinkedIn, I can do that after this call, but I’m telling you, you’re not gonna find something super meaningful over there. It’s been years since I updated it.
27 00:08:48.600 ⇒ 00:08:49.919 Kaela Gallagher: Okay, no worries.
28 00:08:51.070 ⇒ 00:09:02.150 Kaela Gallagher: Okay, cool. And, I guess just to give you, like, a little bit more insight into, Brainforge and kind of the role that we’re looking to fill right now.
29 00:09:02.210 ⇒ 00:09:18.179 Kaela Gallagher: So, we’re a data and AI consulting company, so we work with clients across, you know, different industries, mostly, like, small to mid-sized companies, to help with, like, data and AI solutions. Sometimes we’re almost acting as, like, an in-house.
30 00:09:18.180 ⇒ 00:09:28.879 Kaela Gallagher: data team for them, and it’s a longer engagement. Some of them are shorter, and we have, you know, like, a very, concrete thing that we need to deliver on. Either way, very fast-paced.
31 00:09:28.940 ⇒ 00:09:45.239 Kaela Gallagher: We are looking for an AI engineer currently, and for all of our engineers, we need them to have experience being client-facing. All of our engineers are on client calls and, need to be able to
32 00:09:45.240 ⇒ 00:09:50.199 Kaela Gallagher: Speak technical concepts in a way that makes sense to non-technical people.
33 00:09:50.200 ⇒ 00:10:01.140 Kaela Gallagher: And the way that we are structured is that most of our team kind of falls into one of our three service lines. So, we have, strategy, service line, AI, and data.
34 00:10:01.390 ⇒ 00:10:12.550 Kaela Gallagher: So obviously this role would sit on our AI team, and support different AI initiatives we have with our clients. So yeah, curious if that is something that sounds of interest.
35 00:10:13.140 ⇒ 00:10:22.249 Dan Hartley: that’s complete… that’s something that I am completely looking for. I’m like, and that really aligns with how I’ve, like, made my career shift up till now, so yeah, I’m, like, completely onto it.
36 00:10:22.560 ⇒ 00:10:24.899 Kaela Gallagher: Okay, awesome.
37 00:10:25.110 ⇒ 00:10:35.830 Kaela Gallagher: Yeah, we’re also fully remote. Our team is global, but we do work typically, like, Central or Eastern U.S. hours. You’re based in Virginia, right?
38 00:10:36.230 ⇒ 00:10:38.490 Dan Hartley: Yes, I’m in… I’m in Eastern Time.
39 00:10:38.760 ⇒ 00:10:44.359 Kaela Gallagher: Okay, perfect, so you’re all set for that. Curious, like, what kind of…
40 00:10:45.160 ⇒ 00:10:49.079 Kaela Gallagher: AI projects you’re working on in your current position?
41 00:10:49.370 ⇒ 00:11:14.350 Dan Hartley: Okay, so, at this point, if you ask… I mean, like, over the past couple of years, I’ve worked on so many that if you ask me to highlight a pick or pick one, it gets really difficult, so I’ll tell you about it. I’ve worked on… in almost all domains of AI, be it machine learning, deep learning, computer vision, natural language processing, traditional machine learning, data analytics, data sciences, and then, like, over the couple of years, it shifted up to
42 00:11:14.350 ⇒ 00:11:16.000 Dan Hartley: Being more large language focused.
43 00:11:16.000 ⇒ 00:11:40.680 Dan Hartley: being more agentically focused, I’ve experienced in all of that. A few of the products that are still there live. One of the products that I built on was a machine learning-based computer vision-based, mobile application that is used to detect logos in real time. So this was a project I was involved with, even with the client. So, the client hopped in and be like, hey, I really want to detect… I want a machine learning application that could detect logos. I’m like, okay.
44 00:11:40.680 ⇒ 00:11:41.280 Dan Hartley: fight.
45 00:11:41.310 ⇒ 00:12:01.130 Dan Hartley: sounds like a great idea, but why do you want the logos? So he was like, okay, so I have this small idea in my mind that, hey, if a person is walking down the street, and then he pulls out a phone, and then just, like, the phone points out to something that is a brand, and then if it gets recognized, they could run corporate comments on that. So I was like, yeah, okay, that’s fine. So it started off with, 10 logos to start off as a POC,
46 00:12:01.130 ⇒ 00:12:05.990 Dan Hartley: And then it’s scaled up. Currently, the app is live, its name is orgVision.ai.
47 00:12:06.090 ⇒ 00:12:20.830 Dan Hartley: It’s live on the App Store. It currently supports more than a thousand logos, and it is, one of the, one of the, unlike the core challenges was that how it’s gonna scale is, unlike… and I’ll, get into the conversation with some, obviously later on in the next process.
48 00:12:20.830 ⇒ 00:12:39.989 Dan Hartley: But, the good part about it is, the client onboarded… I’m like, like we were growing, and how we went to Glow, we started to get a lot of traction, and the client… one of the milestones were that the client onboarded Cristiano Ronaldo’s brands. They’re in talks with them, and they signed on the deal. That all the brands that Cristiano Ronaldo is endorsing, they’re in the app itself.
49 00:12:39.990 ⇒ 00:12:48.070 Dan Hartley: So they’re in the app as well. So that was a huge win. Apart from that, there’s also generated AI-focused based… I work on, like,
50 00:12:48.070 ⇒ 00:12:57.349 Dan Hartley: multiple RAG-based, RAG architecture-based chatbots. I’ve worked with medical data, where we were just, like, had a lot of unstructured data and converted them into medical insights.
51 00:12:57.350 ⇒ 00:13:11.290 Dan Hartley: to just, like, have them up, making sure that they’re all HIPAA compliant. One other, is TamiEye, that is a medical chatbot for nutritional advice. It’s there, it’s live. It’s just, like, not a simple chatbot that I would say, it’s just, like, a huge entire use case.
52 00:13:11.290 ⇒ 00:13:17.380 Dan Hartley: For every consideration. I’ve also worked in the fashion industry, in the automotive industry, so there’s, like, a lot.
53 00:13:17.520 ⇒ 00:13:18.080 Dan Hartley: Even if it’s.
54 00:13:18.730 ⇒ 00:13:30.469 Kaela Gallagher: Yeah. Yeah, yeah. I think that’s, like, super relevant, like, your wide range of experience there is super relevant to what we’re doing, because, our clients are across a lot of different industries. We have.
55 00:13:30.470 ⇒ 00:13:47.580 Kaela Gallagher: quite a few, like, CPG, brands that we’re working with. We do have, like, a healthcare organization, and a, like, finance is kind of our next, like, target, so we’re looking to sign financial clients, so I think this is all really relevant to what we’re doing.
56 00:13:47.580 ⇒ 00:13:53.680 Kaela Gallagher: Curious, like, as you’re making your… your next move, like, what is most…
57 00:13:53.710 ⇒ 00:13:59.409 Kaela Gallagher: important to you in your next role? Like, what are you kind of prioritizing as you’re interviewing?
58 00:14:00.170 ⇒ 00:14:18.050 Dan Hartley: I think that’s a great question. So, what I’m trying to look forward in my next role is potentially, like, a couple of things. So, I would like to work in a culture where a lot of companies… where change… the very first thing is just, like, change. Change is accepted and adaptable.
59 00:14:18.130 ⇒ 00:14:33.769 Dan Hartley: So, for example, obviously, with AI, you gotta adapt really fast, right? So there’s, like, one technology that’s being there in the market right now, and then you gotta shift, do a shift to another technology, you gotta migrate, you’ve got to make sure that we’re working on a fast pace, right? The other part that I feel like, is…
60 00:14:34.020 ⇒ 00:14:49.550 Dan Hartley: some great communication and a small, compact, tight unit with drive for each and every person has a drive to learn so that we can… we can contribute equally towards the business success. I am a… really a business-focused engineer. I try to just, like, drive impacts.
61 00:14:49.550 ⇒ 00:14:55.050 Dan Hartley: So that it really directly affects the business, and do what’s best for the business.
62 00:14:55.060 ⇒ 00:15:11.429 Dan Hartley: These are the two couple things. Apart from that, I am looking forward to, and be it being an IC or a team lead, whatever that is, if I’m given a chance to be one, I am pretty much looking forward to just, like, build and scale and grow together.
63 00:15:11.820 ⇒ 00:15:16.780 Kaela Gallagher: Okay, awesome. And then compensation-wise, what’s the range you’re looking at?
64 00:15:16.780 ⇒ 00:15:29.640 Dan Hartley: So I am pretty open tours in terms of compensation, so whatever is what you think is the budget for the specific role that you’re hiring for, whenever, in terms of basis, you can just, like, let me know, and I can acknowledge my confirmation if that works for me. So I’m pretty open.
65 00:15:29.860 ⇒ 00:15:42.020 Kaela Gallagher: Yeah, perfect. That’s definitely something we can explore in later steps as well. Any questions? I know we only have a couple minutes left, but any questions that I can help answer for you?
66 00:15:42.020 ⇒ 00:15:49.390 Dan Hartley: Yes. So, what is the… and this could be high level, obviously, so I really want to know, what is the most difficult
67 00:15:49.520 ⇒ 00:15:55.530 Dan Hartley: challenges that you guys think that you’re facing right now. And that’s… that’s gonna be the first one.
68 00:15:56.000 ⇒ 00:16:11.790 Kaela Gallagher: Okay, interesting question. So for, like, transparency, I actually joined a few weeks ago, and I’m leading, like, all of our, our kind of people and recruiting efforts, so definitely the biggest challenge for me has been
69 00:16:11.790 ⇒ 00:16:22.570 Kaela Gallagher: hiring. Like, we have multiple gaps on the team right now, and so I want to extend probably, like, 4 offers in the next couple weeks.
70 00:16:22.620 ⇒ 00:16:25.380 Kaela Gallagher: So that’s been my biggest focus, and
71 00:16:25.470 ⇒ 00:16:45.309 Kaela Gallagher: Honestly, like, I think the team would almost agree with that in a way, like, we just need some more support. People are really busy, and so, yeah, I think bringing in, like, these new team members, we’re looking for an AI engineer, a data engineer, and an analytics engineer. I think those will make a huge difference.
72 00:16:45.690 ⇒ 00:16:52.730 Dan Hartley: Got it, sounds great. And, one of my next questions is, for this specific role, what does success look like in the next few quarters?
73 00:16:53.640 ⇒ 00:17:08.910 Kaela Gallagher: Oh, interesting. Honestly, like, I think success kind of in the short term coming into Brainforge is all about hitting the ground running. Like, we need people that have a high sense of agency and are comfortable taking on
74 00:17:08.910 ⇒ 00:17:21.569 Kaela Gallagher: projects almost immediately. We just work really quickly, and obviously I’m building out an onboarding process to make sure that you have all the tools you need to be successful, but, yeah, really about hitting the ground running.
75 00:17:21.869 ⇒ 00:17:30.939 Dan Hartley: Got it, thanks. And my last question is just about the process, so if you could just, like, guide me through on how the next trips are gonna look like, and we can hear from there.
76 00:17:31.110 ⇒ 00:17:48.109 Kaela Gallagher: Yeah, perfect. I should have, remembered to go over that earlier. So we do a three-step interview process. So, first one, you’d meet with Sam, just kind of like a cultural, interview, just an overview of your background. He might get into a couple technical things.
77 00:17:48.110 ⇒ 00:17:53.859 Kaela Gallagher: But then the second round is really more the technical interview that,
78 00:17:53.990 ⇒ 00:18:09.180 Kaela Gallagher: It doesn’t involve, like, any live coding or anything like that, but really diving deeper into your technical skills, and because our engineers, like, join client calls, it’s really, like, can you explain these technical concepts in a way that,
79 00:18:09.220 ⇒ 00:18:21.059 Kaela Gallagher: Makes sense. And then, final round, we actually give you, like, a take-home challenge, and you will bring that to the final panel, present your solution and, you know, why you chose it.
80 00:18:21.060 ⇒ 00:18:33.600 Kaela Gallagher: And then, the final panel will include our CEO, and they’ll kind of just ask some questions about your solution, understand your reasoning, and again, like, if you can, you know, present technical ideas.
81 00:18:33.630 ⇒ 00:18:34.310 Kaela Gallagher: Yeah.
82 00:18:34.310 ⇒ 00:18:39.269 Dan Hartley: Got it, got it, yeah, that sounds pretty reasonable. Yeah, okay, makes sense.
83 00:18:39.310 ⇒ 00:18:45.100 Kaela Gallagher: Yeah, right after this, I’ll get that first round, like, link sent over to you.
84 00:18:45.110 ⇒ 00:19:02.649 Kaela Gallagher: And then if you would be willing to send me your LinkedIn, I just like to have that on hand for, our interviewers, and yeah, we should be able to get, I would say, like, the first and second rounds done next week, and then maybe the final the week after. Like, we can move this process along fairly quickly.
85 00:19:02.650 ⇒ 00:19:06.150 Dan Hartley: Definitely, definitely, for sure, for sure. I am just…
86 00:19:06.400 ⇒ 00:19:22.069 Dan Hartley: confused on the LinkedIn part, because that’s pretty much empty, so I feel like that might raise something, that, okay, is this really someone who has much experience? So, okay, I’ll just, like, go back to my LinkedIn, I’ll check, and I’ll just.
87 00:19:23.170 ⇒ 00:19:24.330 Kaela Gallagher: Okay, cool.
88 00:19:24.330 ⇒ 00:19:34.480 Dan Hartley: If for some reason, I just, like, let you know, hey, please, if I can just, like, skip the LinkedIn part, please do not, please bear with me, because I know that’s pretty empty.
89 00:19:34.480 ⇒ 00:19:36.580 Kaela Gallagher: Yeah. Okay.
90 00:19:36.580 ⇒ 00:19:37.399 Dan Hartley: They did it that…
91 00:19:38.100 ⇒ 00:19:52.900 Kaela Gallagher: No worries. I do have your resume, too, from the LinkedIn, or from the email that you sent over, so, I can make sure our interviewers have that, too. What else do you have on your plate right now? Like, do you have any other interviews on calendar?
92 00:19:53.430 ⇒ 00:19:58.459 Dan Hartley: I am in technical rounds with two companies, but…
93 00:19:58.480 ⇒ 00:20:16.110 Dan Hartley: Like, we had this conversation, I think I’d be really interested to explore these, and just, like, check out the tickling rounds go, so I’d be really willing to just expose this further. So, yes, this one is on my list, because it really resonates with how I want to see my career in the next couple of years, how, what my vision is.
94 00:20:16.110 ⇒ 00:20:23.419 Dan Hartley: I think it pretty much resonates with what you guys are doing, so I really want to be a part of a culture where it’s just like, it’s a win-win for both.
95 00:20:23.420 ⇒ 00:20:34.909 Kaela Gallagher: Yeah, yeah, okay, awesome. The reason why I ask is just let me know, like, if any of those get closer to final stages, and, you know, you might have offers on your plate soon.
96 00:20:34.910 ⇒ 00:20:35.500 Dan Hartley: There we go.
97 00:20:35.800 ⇒ 00:20:36.920 Kaela Gallagher: Okay, perfect.
98 00:20:37.110 ⇒ 00:20:39.680 Dan Hartley: I’m definitely just, like, looking forward to exploring this.
99 00:20:39.860 ⇒ 00:20:40.980 Kaela Gallagher: Okay, okay.
100 00:20:41.180 ⇒ 00:20:48.410 Kaela Gallagher: Awesome! Well, thanks so much for your time today, I appreciate it. Great getting to know you, and yeah, we’ll be in touch, soon.
101 00:20:48.790 ⇒ 00:20:51.050 Dan Hartley: Likewise, Kella, and you have a great day.
102 00:20:52.010 ⇒ 00:20:53.659 Kaela Gallagher: Thanks, you too. Bye, Dan.