The best technology teams don’t just care about what they build. They care about who gets to build it, how decisions are made, and whether people feel able to do their best work.
That matters even more when the systems being built support complex, high-pressure environments. At BAE Systems, technology has to be reliable, thoughtful and built by teams who can bring different perspectives to the table.
Phil sat down with three people from BAE Systems who all came into tech from very different directions: Johanna, Chief Data Officer; Davinder, Software Engineer; and Emma, Business Relationship Manager.
Johanna started out wanting to become a primatologist before moving from science and academia into data, AI and transformation. Davinder took the more traditional computing route, starting with a GCSE traffic light system and a computer from her uncle at 14. Emma’s background was in sports coaching and development before a call centre role became the start of a career in IT, service management and business relationship work.
Different paths. Different roles. One very clear theme: the work only really works when people, technology and culture move together.
Tech careers are rarely as linear as they look from the outside. Some people find their way in through formal computer science routes. Others arrive through science, service roles, leadership, operations or completely different industries.
That range of experience is valuable, especially in organisations where technology has to solve complicated human problems as well as technical ones. A strong team needs people who can write the code, understand the data, connect with users, translate business needs and spot the issues others might miss.
Johanna’s route into data started with science. Before becoming Chief Data Officer at BAE Systems, she trained as a scientist and comparative psychologist, then used her quantitative skills and research background to move into data, AI and transformation.
"Very few people come directly into tech and stay in tech all of their lives. So it's really looking at different skill sets and how you get to where you are."
Emma’s career shows that same point from a different angle. Her background was in sports coaching and development, before a call centre role became the start of a path into IT, service management and business relationship work.
That kind of people-first experience matters in a role that sits between business needs and technology delivery. As a Business Relationship Manager, Emma spends much of her time understanding what teams are trying to achieve, connecting the right people and helping prevent problems before they become bigger issues.
"Good translation is being a little bit ahead of the game, I think, because the fires occur when we don't know something's coming."
For anyone wondering whether their background "counts" in tech, this is the useful bit: technical teams need more than one type of thinker. They need people who can bring different skills into the room and make the work stronger because of it.
Not everyone wants to move away from the code.
Davinder has been working in software engineering for more than 30 years, and her career is a good reminder that progression doesn’t have to mean moving further away from the work you enjoy.
The logic, the problem-solving, the moment when something breaks and you follow the trail until it makes sense again. For some engineers, that is the part they want to stay close to.
"if you have a passion for problem solving, just problem solving and using logic... that's what coding is all about."
That’s a side of progression that often gets missed. In tech, "growth" is sometimes treated as a move into management. But staying close to the code can be its own path, and an important one.
Experienced engineers still shape the people around them. They support junior colleagues, guide people through problems and help teams build confidence. The difference is that they do it while staying connected to the part of the work they care about most.
For engineering teams, that matters. You need leaders, but you also need people who deeply understand the systems, care about the detail and want to keep building.
Some technology is visible. You tap, click, scan or search, and the product is right there in front of you.
Other technology sits quietly behind the scenes. It supports decisions, connects information, keeps services moving and helps people do their jobs in complex environments. Most users will never know who built it, tested it or improved it. They just need it to work.
That sense of responsibility runs through a lot of the work at BAE Systems. The organisation operates across serious, high-pressure environments, where data, AI, software engineering and transformation are tied to real outcomes.
For a Chief Data Officer, that means thinking beyond dashboards or reporting. Data fluency is about helping people understand what is happening across the business, where the risks are, how information moves through systems and how better decisions can be made.
For a software engineer, the impact can feel much closer to the code itself. Davinder described the pride that comes from knowing her work sits behind systems people use in everyday life, often without ever thinking about the person who built them.
That’s one of the interesting things about this kind of technology. When it works, most people never notice. But behind that reliability are teams making thousands of careful decisions, from how information is presented to a user, to how systems are tested, reviewed and maintained over time.
Inclusion can sometimes get treated as something separate from the technical work. A culture topic. A values topic. Something that sits around the edges of delivery.
But for teams building complicated technology, it is much more practical than that. People do better work when they feel safe enough to ask questions, challenge assumptions, admit when something has gone wrong and bring their full perspective into the room.
At BAE Systems, that shows up in formal networks and everyday team habits. Emma works with OutLink, BAE Systems’ LGBT employee resource group, alongside her main role. The group helps challenge the business in a healthy way, support colleagues and make sure people feel safe and included at work.
It also shows up in how teams work with neurodiversity, cultural differences, women in technology, family responsibilities and leadership structures. An inclusive team is not just one that has different people in it. It is one where those people are actually heard.
That is especially important in technology, where the person closest to the problem may not be the most senior person in the room. Good ideas can come from different grades, different roles and different lived experiences, but only if people feel able to speak.
If people don’t feel comfortable, they are less likely to share ideas, ask for help or bring their full thinking into the work. Inclusion is not just policy. It is how people talk to each other, how they support colleagues, how they respond when something breaks and whether people feel safe enough to contribute fully.
Technology still has a gender imbalance, especially in technical teams and leadership roles. That matters for progression, but it also matters for the work itself.
Teams building data and AI systems need a mix of experiences and perspectives. If the people shaping, reviewing and questioning those systems are too similar, the work can become too narrow. Better representation helps teams ask better questions, spot different risks and build technology with more people in mind.
There has been progress. Many women working in technology today are following the people who had to be the first or only woman in the room for years. But progress does not mean the problem is solved.
There are still practical barriers that affect whether women stay in the industry, move into leadership and keep building their careers over the long term. Family responsibilities, health, confidence, pensions, part-time work and career breaks all shape the decisions people make. They also shape who gets to keep progressing.
That is why support has to look at the whole person, not just the role they hold today. Visibility matters, but so do the structures around it: mentoring, leadership pathways, flexibility, honest conversations and a culture where women can keep putting their foot in the door without having to fight the same battle every time.
No modern tech conversation gets very far without AI. But the most useful conversations are usually the grounded ones.
For organisations, the challenge is not just choosing a tool. It is getting AI into real operations in a way people understand, trust and can actually use. That means thinking about business change, data quality, governance, ethics and the human judgment that still needs to sit around the technology.
Johanna summed up the adoption challenge clearly:
"The only value that comes out of all of our systems, AI is the same, is if it's used."
That is the bit many organisations still underestimate. AI adoption depends on people understanding what the tool is for, trusting the outputs enough to use them, and having the right data underneath it all.
It also depends on knowing when not to accept the first answer. Davinder gave a practical engineering example: using AI to help with code, then deciding the first solution was too complicated to maintain and asking for a simpler one instead.
That might be one of the most useful AI lessons in the whole conversation.
AI can suggest. People still need to judge.
In engineering, that means asking whether the code is maintainable, whether another person could pick it up later, and whether it actually solves the problem in the right way. It also means keeping human checks in place, like code reviews and pull request reviews, so teams are not just accepting something because "the robot said, do this."
The picture that emerges is of a place where the technical work is serious, but the people behind it are very human.
There are huge data, AI, software engineering and transformation challenges. There are systems being built and supported across complex environments. There are teams thinking carefully about reliability, usability, ethics and long-term impact.
But there is also room for squiggly careers, hands-on engineering, employee networks, inclusive team habits and honest conversations about what it takes to build technology well.
For anyone thinking about a career in tech, that combination matters. You want interesting problems to solve, but you also want to work with people who care about how those problems get solved.
That combination is what makes the work feel real rather than abstract.
Watch the full conversation with Johanna, Davinder and Emma to hear more about their paths into tech, the work they do at BAE Systems, and how inclusive teams help build technology people can rely on.