When Sarah joined the Jarvis Talent Incubation program, she wasn't sure the opportunity was legitimate. Today, she's a full-time developer at National Bank of Canada, where her work has reshaped how the team thinks about AI. 

Every quarter, we sit down with a graduate of Jarvis' Talent Incubation program to talk about their journey, what worked, what surprised them, and what they'd tell the next cohort. 

This quarter's Rising Star is Sarah Primavera, a Vanier College computer science graduate who came into the Talent Incubation program like a lot of new grads do: with a computer science degree, a rough job market, and a fair bit of skepticism about what a "consulting program" actually meant.  

Sarah joined as a developer, was placed with National Bank of Canada, and has since converted to a full-time role there. Along the way, she became the sole Python developer on a ten-person team, ran an internal experiment on how her team was using AI, and ended up presenting her findings to a room of the bank's executives, work that directly shaped how the bank now approaches AI-assisted development. 

Her story is a useful one for anyone weighing whether a Talent Incubation program is worth the leap: what it's like to walk in as a junior on a team that's still figuring things out itself, and what it takes to turn that uncertainty into real influence. 

Here's our conversation, lightly edited for length and clarity. 

IN HER OWN WORDS 

Q: Before you joined, you mentioned the Jarvis Talent Incubation program sounded a bit like a scam at first. What was behind that hesitation? 

I'd had an experience with another company that ran something similar to Jarvis' training. They said experience didn't matter, just a technical background, and some of the reviews I found were rough. People talked about having to pay thousands of dollars to get out of their contract, and the interview process felt rushed and impersonal. That coloured how I felt about consulting in general. When I looked into Jarvis, there weren't many reviews out there either, so I wasn't entirely sure what I was walking into. The one review I did find was from an older version of the program where trainees weren't paid during training, so that added to my hesitation. 

Q: What were you hoping to get out of the program when you first joined? 

Honestly, I was just going with the flow. It wasn't a guaranteed job right away, but I knew it could lead somewhere, and I was happy to be part of something. I was open to wherever it would take me. Looking back, it really was a stepping stone. I'd just finished school and needed a next step, but I was also genuinely open to learning. At Jarvis I was working in Java, and it had been a while since I'd touched it, so the program gave me a chance to refresh those skills and get exposed to some newer technologies my degree hadn't covered. 

Q: You were placed into a pod with Caleb as your trainer. What was that experience like? 

Really positive. My pod was all developers, all working toward placement at the bank. There was one other woman in the pod, and while this industry is male-dominated, I never felt intimidated. I went in with the mindset that we were all on the same level, all recent grads looking for our first break, and nobody treated me any differently. Caleb was consistently supportive. We built a real rapport beyond just the technical material. He'd ask what I had going on outside of work, and when I was visiting Toronto he gave me restaurant recommendations. He was always available for questions, technical or otherwise. 

Q: Did the mock interviews and soft skills training feel useful at the time? 

The mock interviews, or MCRs, definitely helped. Even knowing it wasn't a real interview, it was still nerve-wracking. You're sharing your screen, someone's watching you code, and you have to explain your thought process out loud. That pressure translated well to the real thing. 

The soft skills side, I'll be honest, less so. I think I already had a lot of those instincts, so a lot of it felt like reflection rather than skill-building. I don't think you can fully build those skills outside of actually living through the situations with real people and different personalities. 

Q: What was it like walking into the bank as a junior developer? 

I wanted to absorb everything immediately, which isn't realistic. I remember asking on day one what exactly I was coding for and still not fully understanding. It takes weeks to get your footing, but I wanted it right away. 

What made it a bit different from a typical junior experience was that my team, about ten people, didn't have anyone else working in Python. I was the only one. My manager even said, "you're junior, but you're kind of our Python expert." So rather than leaning on a senior teammate, my team and I were figuring things out together as we modernized some of our older systems and moved them over to Python. It meant we were building standards and processes at the same time I was learning the codebase. 

Q: Tell us about the AI project that got you in front of the bank's leadership. 

My team's mandate is modernizing legacy code, and AI was becoming a bigger part of how people approached that. I noticed leadership's mindset at the time was treating AI almost like a magic box: hand it a huge chunk of code and expect a clean, bug-free result back. That frustrated me a bit, because I didn't think that was realistic. You have to be intentional about how you use it. 

So, I ran a small experiment. I took a large piece of legacy code and gave the whole thing to an AI tool in one go. It handed back something like a thousand lines, and honestly, it was too much to properly evaluate, so I set it aside. Then I re-did the same work my way: breaking it into smaller pieces, working through it bit by bit. Within a couple of days, I had a much leaner, cleaner result that I was confident in. 

I brought both versions to my manager. He liked what he saw enough to ask me to write it up, and it moved up the chain from there, a team meeting, then a meeting with other executives, where I presented my approach and findings directly. 

Q: What changed at the bank as a result? 

The mentality shifted from treating AI as a solution to treating it as a tool, something that speeds up the work rather than replacing the thinking behind it. Around the same time, the bank was also winding down a contract with an outside vendor that had been building an AI agent but wasn't making progress. That wasn't because of my findings specifically; it just wasn't going anywhere on its own. But between the two things, the bank decided to bring AI tooling in-house instead, licensing GitHub Copilot for developers rather than outsourcing to a third party. 

Q: What's your take on AI in software development more broadly? 

A bit of both good and bad, honestly. It's a genuinely useful tool, but I've seen people lean on it as a crutch. You can often tell when someone's code is entirely AI-generated, there's no personal style to it; it just reads as "AI style." You still have to read what it gives you, understand it, and make sure it isn't quietly deleting something important. There are enough horror stories out there to justify that caution. 

I compare it to the internet in general. Before it existed, research meant the library. When the internet first showed up, people worried it would make us lazy or that we'd trust the wrong sources. It's the same cycle every time something new comes along: hesitation first, then it becomes the norm. 

Q: Now that you've converted to full-time at the bank, has much changed day to day? 

Not really, which is a good thing. I'm on the same team doing the same work, just formally part of the organization now. 

Q: Looking back, do you think the two years in the Talent Incubation program set you up well for your career? 

Definitely. It would have been a strong line on my CV even if I'd moved on somewhere else after, and it would have helped me land another role if I'd needed to. I'd absolutely recommend the program to others. 

Q: Any advice for someone considering joining the Talent Incubation program? 

Go in knowing it's not an instant job, it's a process that takes a few months. Be patient and actually use your mentors. They're there to answer your questions, so ask them. 

Q: Anything you think the program could add, now that you've seen the other side as a full-time team member? 

The bank leans heavily on AWS, and I know the Talent Incubation program has been pushing certifications in that direction, which is worthwhile. I'd also point to things like Kafka topics and streaming data. I understood the concepts going in but had never actually worked with them hands-on. 

The bigger gap for me is deployment. There's always a big focus on writing code that works on your own machine, but the steps to actually get something into production, building that environment, are something I'm still building confidence in as a developer. Even a small module at the end of a project focused on deploying a piece of work to production would go a long way. 

Sarah's story is a good example of what the Talent Incubation program is designed to do: take strong technical fundamentals and pair them with real, high-stakes project experience. From her first day of uncertainty to presenting AI findings to bank executives, Sarah's growth reflects the kind of hands-on, mentorship-driven learning that defines the program. 

Interested in joining the next cohort or partnering with Jarvis to build your team's technical talent pipeline? Visit jarvis-talent-incubation.ca to learn more.