Introducing Inside Entrust Identity

We make a lasting impact on the future of identity

People need to prove who they are all the time: to open a bank account, recover access to an account, start a new job, buy a home, access healthcare, or move money.

Most of the time, that process should feel simple. The difficulty is making it simple without making it easy to abuse.

That has become much harder. Fake documents are easier to create. Deepfakes are getting better. Automated attacks are cheaper to run at scale. At the same time, genuine users expect identity checks to be quick, clear and increasingly invisible.

There is no single level of security that works for every situation. Everyday access might require very little from the user. A change in behaviour could trigger a biometric check. A high-risk transaction might need stronger evidence, including liveness detection or additional verification.

Much of the product work is deciding what is appropriate in each situation.

That means working through questions that rarely have simple answers. How much friction is reasonable for the level of risk involved? How should we explain a biometric check to someone who has never seen one before? What happens when the signal is inconclusive? How should the experience behave on an older phone, a poor connection, or in difficult lighting?

These problems cut across product, design, research, machine learning, engineering, security and policy. A decision that looks small in one part of the system can have a large effect on fraud, conversion, accessibility or customer trust.

That is what makes the work interesting.

Who we are

Our identity product team includes engineers, product managers, user researchers, UX designers, technical program managers, data scientists and policy experts.

The work is collaborative because the problems rarely fit neatly within one discipline. A product decision may depend on technical constraints, fraud data, customer behaviour, regulation and the details of the user experience at the same time.

We expect people to bring a point of view, challenge assumptions and help improve the work around them. We also try to create a team where people are straightforward with one another, generous with their time and comfortable asking for help when they need it.

We’re looking for people who can:

• Take an ambiguous problem, work out what matters, and turn it into something useful for customers and the business.
• Care about the quality of the work and help the people around them improve it.
• Influence decisions beyond their immediate team, whether those decisions involve product, technology, design or operations.

Why the work matters

• AI is changing both how we build and what we are defending against. Attackers can automate more of their work, synthetic content is becoming easier to produce, and customers are starting to expect very different things from software. AI also changes how people may interact with identity products in the future. We are having to rethink some of the assumptions that have shaped this industry for years.
• What worked 18 months ago may not work now. Fraud techniques change quickly, new attack patterns appear, and expectations around speed and convenience keep rising. Teams have to keep learning, testing and revisiting decisions rather than relying on a fixed playbook.
• Most of the difficult decisions involve trade-offs. Stronger fraud controls can reduce conversion. More data can improve confidence but increase latency. Additional checks can make an experience safer while making it more frustrating for genuine users. There is rarely one correct answer, so product, engineering and design have to work out which compromises make sense in each context.
• Identity impacts real people at critical moments. They may be opening an account, recovering access, starting a job or sending money. A verification step is only one part of that experience, but it can determine whether they are able to continue. That makes the details important: what we ask for, when we ask for it, how clearly we explain it, and what happens when the system is uncertain.