Top Artificial Intelligence Jobs in Germany

Own end-to-end design and delivery of AI-powered solutions for system transformations. Prototype on the Celonis platform, wire data, compose AI-driven applications, iterate with customers, and scale deployable products across customers while partnering with platform, UX, and GTM teams.

Support validation of Mission Critical Networks in 5G RAN labs and customer networks. Develop and apply AI/ML models to analyze performance, detect anomalies, optimize configurations, and build scripts, tools, and dashboards for automation and visualization. Contribute to proof-of-concepts and collaborate with global stakeholders.

Design and productionize ML systems for advertising using multimodal data (image, video, audio, text, structured). Improve MLOps and data platforms, build scalable data pipelines, monitor models, collaborate cross-functionally, and drive team processes and product impact.

Design and implement end-to-end AI agents and full-stack internal tools, build core AI stack (agent orchestration, RAG, vector DBs), deploy scalable cloud services, lead AI transformation, establish governance, and mentor junior engineers.

Lead and grow strategic automotive customer relationships, drive account planning, forecasting, and commercial opportunities. Coordinate cross-functional teams to deliver customer success, apply AI tools and automation to improve sales efficiency and insights, and identify process simplification and improvement opportunities.

Join Celonis' Orbit graduate program as an AI Solution Consultant to prototype AI+Process Intelligence solutions, run PoVs and hackathons, present business impact to executives, ensure adoption and value realization, and build reusable best-practice assets while specializing in domains like supply chain.

Develop and maintain backend services, mentor team members, support data scientists in ML model deployment, and improve software architecture.

Lead technical design and build production-grade agentic AI systems for logistics, including LLM-based agents, RAG pipelines, and HERE API integrations. Own end-to-end delivery from prototyping to production, write high-quality Python/TypeScript code, design distributed geospatial systems, improve reliability and observability, and collaborate with product and domain experts to operationalize scalable AI solutions.

Support development and rollout of carbon management SaaS solutions. Collaborate with engineering, UI/UX, and compliance to translate regulations into product specifications, gather customer and market feedback, participate in discovery, roadmap planning, and delivery tracking alongside senior product leaders.

Design, develop, and validate state-of-the-art generative and self-supervised ML models for molecular and ligand-based drug design. Apply diffusion/flow-based and representation learning approaches, build predictive models (e.g., binding affinity), work with large proprietary and external datasets, collaborate with computational biology and chemistry teams, and translate research into applied drug discovery solutions while contributing to publications and scientific engagement.

Lead and deliver Pfizer's enterprise AI infrastructure: LLM gateway, model serving, agent runtime, compute provisioning, MLOps, observability, model registry, deployment pipelines, governance/Trust integration, and GxP-compliant auditability across cloud and on-prem environments.

Lead international commercial build for data, engineering and AI: own data foundation, shared engineering pool, solution architecture, AgentOps, AI evaluation, model routing and CIO platform integration to deliver production-grade, governed AI and data products.

The Principal Engineer will lead the design and delivery of core platform capabilities, focusing on scalable systems, AI application, and mentoring engineers while driving architectural decisions and improving operational systems.

Lead business analytics projects partnering with ABB business areas: design data migration, integration, validation, reporting and governance; manage cloud analytics platforms, vendors and infrastructure; pilot AI/ML solutions and ensure alignment with business objectives and controls.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

Lead workshops, architect and design Workday Extend applications, deliver requirements and design to developers, manage and guide Extend consultants, liaise with clients and Workday, and support pre-sales and AI-enabled solutioning.

Lead strategic, post-sale engagements for top customers to drive AI-driven process transformation with Celonis. Own executive relationships, program delivery, adoption, value realization, change management, team mentoring, and cross-functional coordination to ensure measurable business impact and customer advocacy.

The Field CTO will advise C-level executives, lead data and cloud strategy for global accounts, architect innovative solutions, and drive revenue through strategic partnerships.

Lead architecture and delivery of perception and spatial AI models from cloud training to deployment on automotive-grade SoCs. Define deployment-first architectures, productionize state-of-the-art perception research (BEV/multi-camera), set hardware-aware validation metrics, optimize models for latency/memory/throughput, and build and mentor a high-performing engineering team while partnering with research, product, and customers.

Lead customer deployments of Moveworks ServiceNow AI Agents: design and build full-stack AI solutions, integrate and secure enterprise systems, tune LLM-based workflows, drive product adoption, collaborate with product and engineering, produce architecture and solution artifacts, and provide strategic customer guidance. Travel up to 25%.

The role focuses on providing on-the-job training alongside classroom education in Data Science and Artificial Intelligence over three years, culminating in a degree. It includes an internship, language and IT training, and development of personal and leadership skills.

Lead AI strategy and roadmap to integrate AI across R&D for semiconductor product development. Identify productivity bottlenecks, design AI-enabled workflows, run and scale pilots, advise senior leadership, and build organization-wide AI transformation capabilities to improve engineering efficiency, knowledge reuse, and innovation velocity.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

Build and maintain evaluation frameworks, observability, and reliability practices for AI/LLM-powered workflows. Define metrics (SLOs/SLIs), monitor drift and hallucination risk, design guardrails for multi-agent systems, support model selection and platform integration, and collaborate across product, security, and data science teams while participating in on-call rotations.

Lead a Germany-based Global Platform Enablement team to evolve platform capabilities for AI enablement and global support. Drive technical direction for reusable AI platform features, architecture, observability, governance, and developer experience while partnering with cross-functional and US-based platform leaders. Build team capability, guide architectural tradeoffs across automation and agentic systems, and ensure operational excellence and alignment with regulatory and regional requirements.