Resonance · London
Skills: TypeScript, Python
TLDR: We’re looking for top 1%, high agency, AI-forward graduates to join the first graduate cohort at Resonance as Applied AI Engineers. We have recently raised one of the largest ever European seed rounds, with investment from Anthropic and Hg Capital, to deploy AI into the economy and rebuild businesses for the AI era. You’ll work at the frontier and solve real problems in an environment that champions ownership, autonomy and innovation at pace.
Who we are ----------
Resonance is an applied AI company. We have recently raised one of the largest ever European seed rounds, with investment from Anthropic and Hg Capital. Our mission is to close the AI diffusion gap and rebuild businesses for the AI era. We're looking to hire Europe’s elite AI talent.
Why now -------
We believe the economic diffusion of AI is the major challenge of the next decade. Foundation models are advancing far faster than organisations can absorb them; the bottleneck is embedding AI deeply into the core processes of a company to drive an inflection in pace and create organisational advantage. Europe is falling behind on AI, and we exist to help its businesses build real, defensible advantage from it rather than simply adopting it.
The role --------
As a Graduate Applied AI Engineer, you’ll build production AI systems for our clients from your first month, working alongside Senior Applied AI Engineers who review your code and coach you. You’ll ship agents, integrations, data pipelines and evals, working across the stack from the AI layer to the client’s core systems and the interfaces people use. You’ll sit with the people who do the work today, see how AI changes it, and help client teams run and extend what we build. You’ll also contribute to Resonance’s own AI products and shared platform, take on more ownership as you grow, and help shape how we train, build and grow as one of our first graduate cohort.
Your first year: Comprehensive training when you join, covering AI engineering, our platform and…
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