Like every consultancy, we are adapting to an environment that AI is reshaping. Much of the research, analysis and preparation that used to fill a project team's weeks can now be done by machines.

Our clients face the same shift from the other side. Their strategy, technology and IP functions are under a clear mandate to work faster and leaner with AI. But today's landscape of point tools depends on the user to supply the context, and without it the tools speed up the doing without improving the thinking.

What clients still need is sound judgment, grounded in the right context. That is where the real value of AI lies: not in faster work, but in better, more reliable and more impactful decisions. So rather than defend the old consultancy model, we are rebuilding ours around that: consultants who work inside our clients' organizations, supported by an AI platform that holds the client's context. That platform is Sapivia. We are now growing our in-house tech team, to make sure we have the capabilities under our own roof to take Sapivia to the next level.

What we are building: Sapivia

Sapivia is Konsert's AI platform. At its core is the context layer: a client-specific knowledge graph that holds the context every decision depends on. How the business, its technology and its intellectual property connect, what depends on what, and the reasoning behind the decisions already made. We have built that picture for clients by hand for twenty years; Sapivia captures it, keeps it alive and makes it available to people and AI alike.

Our consultants build the context layer together with the client. The client's own people, Konsert's forward-deployed strategists and the AI tools the client already uses can then reason and act on the same picture, one that grows richer over time.

Sapivia is already in use with clients, starting in IP, where the need is sharpest. But the same picture answers the questions every technology company has to ask: which technologies matter, where to compete and how to turn knowledge into advantage. That is where we are taking it next.

The Konsert tech core team

We are building a small tech core team: a handful of engineers with complementary skills. The team is led by a Tech Lead and sits in Gothenburg, next to the consultants who deploy Sapivia with clients. Build work happens in close collaboration with those consultants, several of whom spend part of their time in the team, so the domain expertise and the client's reality are in the room when we build.

We work in an agile way with shared ownership: everyone is close to the users, effort goes where it is needed, and the team ships several times a week and owns the result together. Development runs in close alignment with Konsert's leadership team, with short paths to user input and quick decisions. The tech core team has a central voice in how Sapivia is shaped. Around this core, we scale with external developers and the Rouse Group's technology organization.

Questions we are working on right now

Giving AI the right context is only the start. Turning that context into decisions that large companies can rely on raises questions that few teams have answered yet. These are some of the ones we are working on now. They are open questions, not tickets, and you will help answer them.

• How do we assure the quality of AI responses at scale, when the right answer is often a matter of judgment?

• How do we best combine deep domain knowledge with what the models already know?

• How do we make a rich, connected body of knowledge feel simple and intuitive to work with?

• How do we give large organizations precise control over who sees what, across regions, teams and many users?

• How do we shorten the path from prototype to production code, while keeping the freedom to experiment?

The role: Backend Developer

You bring the backend and platform foundations to the core team: APIs, data models and services that can grow, built in Azure with CI/CD. Our clients are large corporations and their security requirements are part of what it takes to sell the product, so secure by default is a way of working, not a phase. You work on the data layer, including the context graph the applications run on, on tenant isolation and access control, and on how AI features are served and scaled.

What you bring

• Several years (likely 5+) of professional experience as a software engineer

• Strong backend development in .NET and C# and in TypeScript and Node

• Experience designing and running multi-tenant systems, with data isolation, role-based access control and audit logging treated as first-class concerns

• Experience with document and graph databases, for example MongoDB, including data modeling and query performance

• A solid foundation in secure development: authentication and authorization (for example Entra ID), secrets management, secure coding

• Experience with Azure (App Service, Key Vault, storage), CI/CD in Azure DevOps or similar, and infrastructure as code; vector search and API contract design (OpenAPI) are a plus

• Experience using AI tools as a natural part of your development work