Top Artificial Intelligence Jobs in Germany

Design, build, evaluate, and integrate AI-powered services, APIs, agentic workflows, and automation into production systems. Develop backend services (Python, FastAPI/Flask/Django), evaluate and deploy models (LLMs, speech), integrate with internal/external services, support model evaluation/training/fine-tuning, and collaborate with platform and product teams to operationalize AI solutions.

Lead design, training, and evaluation of LLMs for translation and language-quality tasks; build robust evaluation frameworks; architect agentic multi-model workflows; own model development from data curation to production; run reproducible experiments; collaborate with product and engineering and mentor researchers.

Build, prototype, and productionize applied AI workflows for construction projects: manage experimentation pipelines, error analysis, evaluation/scoring, dataset curation, and improve ML/data pipelines and monitoring for complex unstructured data sources.

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.

Design rigorous, deterministic advanced physics problems and provide complete verified solutions for AI training and evaluation. Create reproducible simulations or computational workflows (using Python and scientific libraries), document reasoning clearly, and ensure technical precision. Contribute to problem design that tests deep multi-step physical reasoning.

Own the vision, roadmap, and backlog for the MLOps/LLMOps Platform and AI Service tooling. Prioritize features, run agile ceremonies, steer technical discussions, represent users, manage dependencies and risks, and align international stakeholders to enable data scientists and ML engineers to build GenAI applications.

Lead integration of AI capabilities into the osapiens HUB by gathering and prioritizing application-team requirements, translating business needs into AI solution scenarios, monitoring AI market trends, measuring AI component usage/performance, and building cost structures and business cases to prioritize AI investments.

Own acquisition, onboarding, and activation for JetBrains AI. Improve product entry points, trials, demos, and onboarding flows. Lead experiments, analyze funnels and cohorts, remove friction, and partner with design, engineering, analytics, marketing, and monetization to drive activation and conversion.

Design and implement agentic tools, translating product needs to production, scale prototypes, improve semantic search, build evaluation pipelines.

Design and develop Generative AI applications, building scalable full-stack solutions, managing various libraries, and collaborating across teams to enhance AI user experiences.

Drive market growth of IFS Loops, engaging industrial accounts to sell AI-driven workflows. Lead consultative sales and close high-value opportunities.

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.

Lead development of an autonomous agentic AI scientist for drug discovery: architect multi-step reasoning agents, bridge AI and wet-lab experiment design, prototype to productionize agentic systems, publish research, and collaborate with biological experts.

Support Central Europe Data & Analytics by building consistent KPIs and Power BI reports, analysing leasing, occupancy and financial performance, gathering and modelling data from lakes/warehouses, driving AI tool adoption, supporting systems requirements/testing, and partnering with operations and asset teams to improve NOI, reporting and operational execution.

Design, build, and maintain production-grade AI services and APIs using LLMs and custom models. Develop agentic orchestration, semantic retrieval, and vector search solutions. Implement observability, CI/CD, and scalable distributed systems, write and maintain Python libraries/SDKs, collaborate on architecture and API standards, and mentor engineers.

Manage a global Generative AI program: define scope, plans, and success metrics; oversee Scrum teams, mitigate GenAI-specific risks (accuracy, privacy, cost), coordinate security/legal/compliance, and drive delivery, change management, and process improvements.

Design, implement, and operate scalable Generative AI services, chatbots, and autonomous agents. Deploy and maintain on-prem LLM infrastructure (Docker/Kubernetes), implement RAG and MCP pipelines, ensure security/compliance, provide technical support and documentation, and contribute to AI roadmap via PoCs.

Lead design and implementation of a scalable modern data platform and real-time pipelines. Build, optimize, and maintain data models, ETL/ELT pipelines and integrations (Kafka, Spark, Delta Live Tables), enforce data governance and quality, enable AI/ML workflows and MLOps, mentor the team, evaluate new technologies, and collaborate with product and analytics stakeholders to deliver reliable, self-service data products.

Lead and execute company-wide AI strategy, coach team leads to meet AI goals, shape the AI stack, prototype solutions, report to C-level, and hire and grow an AI team to deliver measurable business value.

Lead data strategy and build an AI-ready, governed, omni-channel customer data foundation. Deliver self-service analytics, graph-based models, identity resolution, and data governance. Hire and grow the data organization and enable cross-functional adoption of data and AI capabilities.

Own the AI platform roadmap and build reusable capabilities (prompting, RAG, tool calling, agents, evaluation, observability). Run discovery, prioritize AI investments, partner with Product, Engineering, Design and Data, guide other PMs, define success metrics, and ensure scalable, reliable AI-powered features that deliver customer and business value.

Produce high-volume, short-form paid social video using AI-first workflows (video generation, AI voiceover, editing). Localise content across European markets, iterate with performance marketing, apply brand guidelines, and maintain platform-specific knowledge for Instagram, TikTok, and YouTube Shorts.

Erasmus-eligible intern to design and build AR/VR apps and an interactive website, manage hardware/software, create AI-assisted media and 3D assets, and support onboarding for art-science projects in Berlin or Saint Martin.

Support curatorial projects at the intersection of art and science using AI tools: develop and organise exhibitions/events, lead communications and fundraising, manage stakeholders, teams, budgets, schedules, risks, and deliverables.

The Chief of Staff will drive company operations, translating strategy into execution, managing financial steering, leading initiatives, and applying AI for operational efficiency directly with the CEO.