Top Artificial Intelligence Jobs in Germany

Design polished, user-centric mobile and web interfaces for BJAK's AI-driven financial products. Translate requirements into wireframes, flows, prototypes and high-fidelity UI. Maintain design system, ensure accessibility and responsiveness, iterate using user feedback, and collaborate with PMs and engineers to deliver pixel-perfect implementations.

Lead and run the enterprise AI orchestration platform: own roadmap and budget, manage AI product delivery and vendors, ensure governance and compliance (EU AI Act, GDPR), drive adoption and change management, and provide technical architecture oversight for LLM integrations and agent frameworks.

Lead short-term AI adoption program: build internal AI champions, create usage policies and training, support teams implementing AI tools, contribute to internal AI tool builds, and ensure responsible, secure deployment across distributed teams.

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.

Lead end-to-end implementations of QVAC-powered AI deployments, coordinating clients, engineering, product, and legal teams; define roadmaps, manage risks, track progress, and ensure production rollout while aligning technical capabilities with business requirements.

End-to-end product engineering owner: identify customer problems, design and ship production-ready full-stack features, iterate from user feedback, use AI tools to speed development, and collaborate closely with founders, engineers, and customers in an in-person startup environment.

Build and scale end-to-end full stack systems for Louco's event discovery platform. Implement personalized feeds, recommendations, search, notifications, ticketing integrations, and AI-powered features. Own features from architecture through deployment, optimize performance and reliability, and collaborate with product and design in a fast-moving startup.

Design and build Enpal's internal AI platform and Agent Runtime to orchestrate production AI workflows. Develop scalable backend services, developer APIs, observability/evaluation tooling, CI/CD and IaC for reliable, reproducible, cost-efficient AI feature delivery. Collaborate with product and engineering teams and drive architectural and quality standards.

Lead and operate the sales process for AI and robotics solutions: identify and qualify leads, run initial customer discussions, manage pipeline and proposals, coordinate with technical teams, hand over projects to project management, and collect market feedback to shape product and business development.

Own and build the internal data warehouse and analytics platform: consolidate product and operational data, define data models and contracts, create transformation pipelines, enable AI/ML datasets, implement data quality, lineage, and observability, and collaborate with stakeholders to support BI and analytics.

Lead research and productionization of generative and representation-learning systems for large-scale recommendations. Build and optimize user/content embeddings, multi-stage retrieval/ranking pipelines, and deploy high-throughput, low-latency models in production while mentoring teammates and driving research direction.

Design and own the platform's knowledge graph and agentic AI pipelines: ingest and resolve entities, implement NER and entity-disambiguation, integrate LLM APIs and AI web search tools, build RAG and conversational graph-interrogation layers, maintain Python data pipelines (Databricks -> Neo4j), and drive evaluation, documentation, and architectural decisions.

Embed with German teams to identify workflow improvements and drive AI adoption. Deliver training, prototype AI automations using no-code/low-code tools, measure outcomes, and act as local AI Operations representative to scale successful solutions globally.

As an AI-native growth hacker, you will implement a growth strategy, focusing on a specific growth wedge, leveraging AI tools, and measuring performance to scale successfully.

Senior Director analyst providing thought leadership and actionable research on infrastructure and operations AI strategy. Produce insights, presentations, and client advisories; guide AI infrastructure, cloud adoption, integration, governance, and vendor selection. Lead research agenda, mentor analysts, collaborate cross-functionally (infrastructure, engineering, enterprise architecture, cybersecurity), support sales, and represent Gartner at events. Drive process improvements and influence senior stakeholders to align infrastructure and operations with business outcomes.

Lead the design and implementation of an AI Business Automation Platform, driving revenue growth through AI solutions while mentoring an elite engineering team.

Post-sales, customer-facing role that drives developer adoption of AI tooling by designing and running hackathons, Customer Developer Days, and repeatable facilitation infrastructure. Partner with deployment and success teams to diagnose adoption stalls, run high-touch interventions, capture outcomes, and evangelize results. Must be technically credible with developers and able to troubleshoot and demonstrate AI coding tools in real time.

As a Lead/Staff Full Stack Engineer, you'll design and develop full-stack applications and AI agents for the GenAI platform, focusing on rapid deployment and impactful decision-making for various industries. You'll also mentor engineers and lead major projects.

As a Principal Full Stack Engineer, lead the development of the GenAI platform, design full-stack applications, and mentor engineers. Build scalable systems for AI agents affecting key industries, ensuring security and reliability.

As a Senior AI Engineer, you will develop AI agents, integrate features into a web app, enhance matching systems, and collaborate across teams to deliver ML solutions.

The Sales Development Representative will identify potential manufacturing customers, initiate conversations, qualify leads, and work closely with Account Executives to enhance sales pipeline and strategies.

Evaluate AI coding agents end-to-end, judging usefulness, high-level correctness, engineering judgment, and quality of explanations. Provide opinionated feedback, distinguish response quality levels, and help define standards for great AI-developer interactions. Participate in take-home evaluation and interview as part of a rolling, project-based engagement.

Design and introduce NVIDIA AI solutions for telecommunications (network management, cloud/edge/NFV), lead technical aspects of complex deployments and PoCs, create trainings and technical content, and drive customer adoption and integration of AI platforms.

Develop and own frontend features for AI-driven, agentic product experiences; collaborate with engineering, product, data science, and AI teams; write clean, testable, secure code; lead technical discussions; and contribute to architecture and scalable foundations across CLI, server, and chat products.

Lead a new AI Engineering and AI Platform team to productionize AI use cases. Provide technical direction for backend, cloud-native architectures, IaC, CI/CD, and agentic workflows. Build platform services for model access, integrations, observability, governance, rate limiting, and cost management. Collaborate with Data Science, Product, Security, and stakeholders; recruit, mentor, and establish engineering best practices for secure, reliable AI systems.