Top Artificial Intelligence Jobs in Berlin

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.

Author and refine a systems-engineering curriculum for experienced engineers: shape syllabus, define learning objectives, produce and fact-check lessons using AI tools, design hands-on projects and rubrics, and iterate with LX designers to meet milestone deliverables over a 4–6 month, ~15–20 hr/week engagement.

Lead applied research and system design for agent-native search: build multi-stage retrieval, ranking, and grounding methods for LLM-driven, iterative agent workflows; deploy high-throughput, low-latency production systems; define evaluation metrics; run experiments and mentor engineers.

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.

Create German-first B2B content (blogs, case studies, landing pages, video concepts) using AI-enabled workflows to educate frontline industrial buyers and drive acquisition; own end-to-end content strategy, production, measurement, and cross-team collaboration.

Own and scale AI enablement: build core orchestration, LLMOps/MLOps platforms and governance, integrate generative AI into product, optimize cost/latency, run PoC-to-production delivery, upskill teams, standardize tooling and vendor strategy, and track adoption/ROI metrics.

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 Oyster's data platform and AI strategy, centralize AI initiatives into production systems, build scalable data and MLOps infrastructure, modernize knowledge architecture and semantic search, partner cross-functionally to embed AI into products and workflows, enforce tooling standards and governance, and drive organizational adoption and change management for AI-assisted operations.

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.

Review, evaluate, and annotate AI-generated multilingual and multimodal content (text, images, audio, video). Perform quality checks, identify edge cases, participate in calibration and alignment, and provide feedback to improve datasets, workflows, and annotation guidelines.

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

Own client relationships and advise on digital marketing using the company's AI tools. Lead marketing strategy, coordinate and manage projects and teams, implement technology to improve ad creative, landing pages, and budget allocation to maximize ROI.

Define product vision and strategy via market research and data analysis; build prioritized roadmaps; collaborate with PMs, designers, and engineers to launch products; communicate with stakeholders; track performance and iterate post-launch.

Support Uplane's marketing efforts by creating AI-generated ads, managing campaigns, conducting research, and providing process feedback to improve AI software.