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Senior Applied AI Engineer

Resonance•Berlin
Full-timeSenior
👁️ 0 views•📝 0 applications•Posted 11/3/2026•Expires 12/4/2026
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Job Description

TLDR: We’re looking for top 1%, high agency, AI-forward senior engineers to be part of our early team at Resonance in Berlin. 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, and we're building our Berlin hub to serve clients across Germany, Austria and Switzerland. 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 Senior Applied AI Engineer in Berlin, you’ll lead Resonance’s most ambitious client engagements across DACH.

You will design and build production AI systems to drive a dramatic acceleration in productivity or a step change in growth for our key clients. You will work at the AI frontier, own end-to-end deployments, and lead a team of AI engineers to build at pace.

You’ll set the technical direction, advising CTOs and engineering leads of leading enterprises and owning security, reliability and governance for everything we put into production.

You’ll lead the build from first prototype to production while staying hands-on in the code, working across the stack from data pipelines and the AI layer

Required Skills

Engineering

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