Top Artificial Intelligence Jobs in Berlin

Lead and build Axelera's AI Infrastructure Systems division to deliver datacenter-class hardware from accelerator cards and OAM/UBB modules to 1U/2U racks. Own architecture, schematics, PCB/layout review, power/thermal/mechanical design, BMC/firmware, bring-up, validation, qualification, NPI, and ramp with CMs/ODMs. Align roadmaps with silicon, SDK, and product teams, engage customers and partners, set engineering processes, manage budget and vendor relationships, and mitigate technical risks through hands-on leadership.

The AI-First Full-Stack Engineer will lead full-stack development using Node.js and Next.js, integrating AI workflows and orchestrating Claude agent teams for efficient engineering processes, ensuring compliance with healthcare standards.

Own end-to-end product for a slice of Nebius AI compute platform: define strategy, APIs, and roadmaps; drive cross-team delivery; conduct structured discovery; measure adoption and platform outcomes; engage engineering as a technical peer; and close operational feedback loops to improve reliability and customer experience.

The Senior Product Manager will own the strategic roadmap, lead market research, manage monetization strategies, and mentor product managers within an AI and EdTech environment.

Own end-to-end design, build, deploy, and iterate on production AI systems that improve lead quality, reduce refunds, and automate workflows. Ship customer-facing AI features, agentic workflows, retrieval and context layers, reliable event-driven automations, evaluation datasets and monitoring, and reusable components while connecting technical decisions to business KPIs.

Build and test AI-agent features and internal agent frameworks for a proactive cybersecurity platform. Implement and integrate generative AI systems (agents and RAG), stay current with AI research, and apply innovations to product development and evaluation within a security-focused environment.

Lead customer-facing implementations of AI-driven chatbots, voicebots, and multimodal assistants on the NICE CXone/Cognigy platform. Configure NLU/ASR/IVR, integrate CRMs and APIs, design conversational flows and personas, run workshops, support UAT and go-live, produce documentation and demos, mentor team members, and optimize post-deployment performance.

Develop and maintain an AI-driven pipeline to auto-generate, process, and publish real-life and digital quests. Integrate AI frameworks, design scalable automation workflows, analyze user data to improve generation quality, build API integrations, participate in architecture and documentation, test with pytest/unittest, and collaborate with cross-functional teams to validate LLM outputs against real-world data.

The role involves evaluating and reviewing AI-generated outputs, ensuring cultural relevance and accuracy, and providing annotations for model improvement.