Research Engineer

About Electric Twin

Most organisations make their biggest decisions on a thin slice of evidence — a handful of customer calls, one survey, instinct when the data runs out. Electric Twin changes that. We're a behavioural simulation platform that lets organisations test ideas, messages, and decisions against synthetic populations — digital twins of real audiences — and get answers in minutes that would otherwise take weeks.

The work is grounded, and the engineering is real. We've run over 40,000 evaluations across populations covering 155 countries. Independent academic research with Professor Michael Muthukrishna at the LSE found our outputs come back roughly 10,000× faster than traditional methods, at 95% accuracy. AI is part of what we build, but it isn't the product. The hard work is system design, data, orchestration, and making outputs trustworthy enough that people act on them. Running population-scale simulations is a systems problem as much as a science one — foundation models, behavioural data, evaluation pipelines, and the infrastructure that holds them together, with real engineering problems at every layer.

How the work gets done here isn't handed down — it's worked out by the people closest to it. You'd help shape what gets built or sold and why, decide where the trade-offs sit between speed and depth, and judge when something is ready for customers and when it needs another pass. What the role involves day-to-day, what your first six months look like, and how compensation, equity, growth and flexible working are structured are all set out in detail below — the headline is that early joiners get meaningful equity, a clear path to grow with the company, and the flexibility to work around the rest of your life.

Electric Twin was founded by Dr Ben Warner (former Chief Data Advisor to the UK Prime Minister) and our CEO, Alex Cooper (a former senior military commander and Director of Mass Covid Testing in the pandemic). We're backed by top tier investors including Atomico, LocalGlobe, Mercuri, and angels including Marc Andreessen. We have a high-class team of engineers, AI researchers, behavioural scientists, and operators — careful with the science, careful with the responsibility.

The Role

As an AI Engineer you will be part of the wider technical team but positioned within Science. You’ll research and build the systems that bring our AI agents to life and you will work with engineering to scale the infrastructure that powers our LLM-driven synthetic populations.
You'll design agent cognitive architectures, implement context engineering and memory systems, while ensuring these AI systems can operate reliably at scale in production environments.

This role balances AI agent research with backend engineering. It is ideal for research engineers who want to work directly with large language models to create realistic behavioural simulations, while building the robust infrastructure needed to deploy them in enterprise settings.