At Qognetix we are building the execution infrastructure for a new category of intelligent systems.
Most modern AI systems operate as statistical inference engines. They generate outputs by prediction rather than by executing governed internal processes over time.
Our approach is different.
We are developing runtime infrastructure in which intelligent behaviour emerges from explicit mechanisms, persistent state, and biologically grounded signal dynamics rather than opaque optimisation alone.
The BioSynapStudio substrate explores how neural-style computation can operate as a controlled, inspectable, and long-running execution environment. This creates the possibility of intelligent systems that are not only powerful, but also understandable, governable, and suitable for integration into real-world infrastructure.
The Foundation Lead Software Engineer will help build the core systems that make this possible.
This role sits close to the architectural heart of the platform. You will work directly with the founders to design the runtime systems, tooling, and software foundations required to turn early technical breakthroughs into a robust engineering platform.
Designing and implementing core components of the BioSynapStudio execution engine
Building deterministic runtime systems for persistent neural-style computation
Developing software that supports long-running, stateful system behaviour rather than simple request-response execution
Creating debugging, introspection, and instrumentation tooling for inspecting internal system dynamics
Contributing to visualisation, runtime control, and developer-facing tooling
Working closely with the founders to translate research and prototype behaviour into maintainable software architecture
Helping define engineering standards, system boundaries, and core development practices
Supporting the evolution of the platform from demonstrator toward production-capable infrastructure
We are looking for an engineer who enjoys building difficult systems from first principles.
This role will suit someone who is naturally drawn to deep technical problems, likes understanding how systems behave over time, and is comfortable working in an environment where the architecture is still taking shape.
The strongest candidates are likely to be people who:
enjoy reasoning about complex systems rather than treating them as black boxes
are comfortable moving between architecture, implementation, and debugging
prefer building foundations over shipping isolated features
can think carefully about performance, stability, and long-running behaviour
are excited by the idea of helping define a new computing platform rather than joining an already mature stack
are curious about the intersection of computation, neuroscience, runtime systems, and intelligent infrastructure
We value technical curiosity, engineering judgement, and clear thinking more than checklist-driven career profiles.
Strong software engineering experience, ideally in systems, platform, or infrastructure-oriented roles
Experience designing and implementing maintainable, well-structured software systems
Strong understanding of concurrency, asynchronous execution, and stateful behaviour
Confidence debugging complex technical issues across multiple layers of a system
Ability to work effectively in an early-stage environment where priorities and architecture continue to evolve
Strong communication skills and the ability to reason clearly about technical trade-offs
Experience with C# / .NET and related tooling
Experience building runtime systems, simulation environments, or other performance-sensitive software
Experience with instrumentation, diagnostics, observability, or developer tooling
Experience designing software that must behave predictably over extended execution periods
Experience with graphics, visualisation, or interactive system tooling
Experience with scientific computing, modelling, or simulation systems
Familiarity with computational neuroscience, biologically inspired computing, or emergent systems
Experience with distributed systems, high-performance systems, or platform engineering
Experience creating internal tools that improve the productivity of technical teams
Qognetix is still at the stage where core technical decisions have real leverage.
Joining now means working on the first generation of the platform while the architecture is still being actively shaped. Rather than contributing to a mature codebase with fixed boundaries, you will help define the systems, tooling, and engineering practices that the platform will grow on.
This is an unusual opportunity to work on something genuinely foundational.
You will be helping to build the execution substrate for a new approach to intelligent systems, working closely with the founders on software architecture, runtime design, tooling, and technical direction.
For the right engineer, this role offers the chance to do work that is both technically demanding and strategically meaningful.
