Top Artificial Intelligence Jobs in Germany

The Sales Manager will drive market entry and customer journeys, identify opportunities, manage sales processes, and lead a team while handling 50% travel.

The intern will assist with EdTech solutions analysis, research trends, and support market analysis efforts while collaborating with the team.

Drive product marketing for Renesas automotive microcontrollers: gather global customer requirements, coordinate projects with OEMs/Tier1s, define roadmaps, support sales and support teams, manage product introductions and marketing materials, report KPIs, and coordinate with Japan.

Own partnership sourcing, negotiation, and deal execution to drive adoption of Walrus across AI and Web3 ecosystems. Build relationships with AI builders, data vendors, compute networks, and web3 partners; lead contract negotiations; and manage cross-functional integration from signing through execution.

Drive development and deployment of AI solutions, translating business needs into product requirements, managing backlogs, and coordinating cross-functional teams.

Lead enterprise AI strategy, operating model, governance, platform enablement, and CoE to deploy safe, compliant, and scalable AI across R&D, Clinical, Manufacturing, Quality, Commercial, and Corporate functions in a regulated pharmaceutical environment.

Lead end-to-end architecture and integration of battery insights algorithms into production embedded systems. Define modular architectures, drive algorithm development (signal processing, ML, modeling), translate algorithms to real-time software, guide cross-functional teams, mitigate risks, and mentor engineers to ensure scalable, maintainable, production-ready BMS solutions.

Lead design and ownership of shared libraries, Spring Boot starters, and agentic frameworks. Set standards for agent orchestration, evaluations, and guardrails. Mentor teams on Python-based agents (LangChain/LangGraph), drive adoption, prototype research directions, and improve developer experience across Kotlin backend and client libraries.

Lead architecture and execution of data platforms and LLM-powered products: design and scale data pipelines, integrate and deploy models, define engineering standards (testing, evals, observability, SLOs), mentor engineers, drive cross-functional delivery, and optimize reliability, cost, and product outcomes for enterprise customers.

Design and build production-grade AI/LLM backend services and APIs, integrate third-party LLM APIs, develop cloud-native architectures on AWS, extend Terraform and CI/CD pipelines, implement testing/monitoring, and build agentic orchestration workflows.

Constructor University offers Ph.D. positions for MSc graduates in Computer Science focusing on AI and ML, including research and an industrial internship.

Serve as first-line technical customer success for self-serve users, resolve inbound tickets, triage bugs, monitor usage to prevent churn, surface recurring friction to product/growth, reproduce and document issues, and help build in-product help to reduce support volume.

Provide hands-on customer success and technical support for AI legal SaaS users in the DACH region: respond to inbound tickets, triage and reproduce issues, monitor usage to prevent churn, surface product insights, and improve self-serve help to drive adoption of the Legal AI Suite.

Design and implement automations and scalable workflows; work with data and automation tools; build autonomous agent systems for pricing, market analysis and forecasting; manage projects end-to-end; design data architectures and maintain clear documentation to deliver measurable business impact.

Lead the planning, execution, and delivery of robotics projects, coordinating cross-functional teams and managing budgets, timelines, and risks.

Lead new-business enterprise sales within an assigned territory (≈70% new logos, 30% account growth). Prospect, qualify, and close complex deals with C-level IT and business stakeholders using value-based selling, ROI/TCO models, MEDDPICC/MEDDIC, and coordinated cross-functional support to exceed quota and develop referenceable customers.

Lead end-to-end product design for an agentic incident-management platform: design human-AI collaboration patterns, simplify interfaces for crisis triage, create data visualizations and mobile-first experiences, evolve the design system, and deliver Figma prototypes from research to production.

Build, improve, and deploy AI agents and automation workflows for Enpal's energy platform. Convert manual processes to agent-driven flows, debug tool-call issues, collaborate closely with ops and engineers, iterate quickly, and ship reliable, cost-effective agent solutions.

Build and productionize generative-AI creative pipelines: design node-based automation and AI agents, fine-tune models (LoRAs), generate video/audio/visual assets at scale, integrate models via APIs into DAM/UGC systems, iterate using UA and data insights, and continuously R&D new image/video/audio models and techniques.

Lead and scale an existing AI and automation programme across finance: set strategy, redesign processes for agent-first operation, deliver measurable impact, build and ship agents or integrations, manage a small team, and roll solutions across five markets while reporting to the Group CFO.

The intern will assist in AI research focused on semantic structure extraction and content generation, supporting data analysis, experiments, and documentation.

Lead end-to-end ML product roadmaps and initiatives (e.g., Attachment Matcher, Transaction Categorizer). Collaborate with data scientists, engineers, and stakeholders to define, deliver, and monitor ML solutions that drive measurable business value for SMEs across Qonto's platform.

As a Senior AI Engineer, you will design and deploy LLM-powered and GenAI systems, collaborating with stakeholders and ensuring production readiness.

As an AI Solutions Engineer, you will design and implement AI-driven automations to enhance workflows and eliminate bottlenecks, collaborating across teams to innovate solutions.

Provide EU-focused counsel on AI and privacy regulation (EU AI Act, GDPR, DSA); draft policies, DPA and contractual terms; translate legal requirements into technical and operational controls; advise product, engineering, and go-to-market teams; liaise with regulators and manage compliance programs and risk assessments.