Top Artificial Intelligence Jobs in Germany

Build and ship in-product AI capabilities: integrate LLMs and RAG, design prompting and evaluation, implement MLOps/LLMOps, ensure production reliability, privacy, and compliance, and collaborate with data, platform and product teams to move AI from prototype to production.

Lead a global team of solution specialists to drive growth across AI Business Solutions, Security, and Business Process. Coach and develop specialists, engage strategic customers and partners (including Japanese enterprise accounts), manage pipeline and forecasts, scale cross-region GTM best practices, and deliver measurable revenue, transformation, and operational outcomes across complex, multi-region environments.

Build and operate large-scale Azure AI services for multimodal model inference (audio, image), design scalable distributed architectures, debug and optimize across the stack, operate global cloud services, collaborate with partners, and drive technical excellence with full-stack ownership from infrastructure to APIs.

Build and ship production-grade AI features and agent/LLM-powered workflows for analytics and data engineering. Rapidly prototype, iterate with users, integrate with internal tools, and ensure scalable, observable solutions.

Lead regional strategic initiatives and PMO activities across Europe, establish governance, simplify processes, drive AI-enabled productivity, coordinate executive forums, and communicate change to deliver measurable business outcomes.

Lead planning and delivery of high-priority regional initiatives across Europe. Enable executive governance, simplify regional processes, embed AI-enabled ways of working, drive communications and stakeholder engagement, and strengthen the Europe Business Impact Team to ensure measurable business outcomes.

Define the vision and roadmap for an Agentic AI platform, prioritize platform capabilities (LLMOps, MLOps, observability, governance, secure AI), and partner with engineering, data, security, and business teams to build scalable, reliable, and easy-to-adopt platform services on Azure using IaC and CI/CD.

Responsible for driving business development of AI products, managing the sales cycle, building client relationships, and ensuring contract negotiations are completed.

Record short video and audio clips and transcribe or capture text from media to provide expressive, tonal examples for AI training. Projects may require acting short scripts in varied emotional styles. Remote, project-based work with variable hours.

Manage various AI/ML projects from concept to development, coordinating teams, managing risks, and ensuring project goals are met. Responsible for documentation and financial planning.

The Backend Engineer will design, develop, and maintain backend services with AI/ML capabilities, focusing on scalability, performance, and optimization of APIs and distributed systems.

Join AutoScout24 as a Software Engineer / AI Enabler to build impactful AI-driven products, coach teams on effective AI usage, and improve software delivery processes.

Join AutoScout24 as a Software Engineer to enhance their technology stack, optimize systems, and integrate GenAI tools into applications, driving efficiency and quality.

Own product and go-to-market strategy for GPU and AI services: define roadmap, pricing, packaging, and target segments; convert customer research into engineering backlogs; act as technical lead for enterprise accounts; monitor competitors and work with sales and channel partners to scale commercial adoption.

Record short video and audio clips and perform brief scripted or improvised vocal performances with varied tones and emotions. Listen to and transcribe or capture text from clips. Work remotely on a flexible schedule using a quiet recording environment and basic video equipment.

Design and ship AI-driven controlling tools, own the group data foundation, automate monthly closing processes, translate complex cost data into CFO/board-level narratives, and ensure integrity of controlling figures.

Partner with business and data teams to identify high-value AI use cases, design and prototype LLM-based solutions (RAG, agents, prompts), integrate with enterprise data via Azure Databricks, and drive adoption through change management and scalable deployments.

Lead a delivery lane for forward-deployed AI engineering, hire and manage a decentralized team, drive production ML/AI automation (50% hands-on), standardize templates/skills, and coordinate stakeholders to accelerate domain onboarding and business impact.

Lead end-to-end development of production-ready AI and LLM solutions: identify use cases, design architectures, implement and deploy models (RAG, embeddings, fine-tuning), experiment with new models and tools, collaborate with clients and stakeholders, and mentor junior team members.

Design and implement scalable AI and generative AI solutions, build multimodal agents and automated workflows, develop MLOps tooling and deployment pipelines on cloud platforms, write maintainable code, document processes, and present results to stakeholders and clients.

Build production-grade AI agents, LLM apps, RAG systems and automations for fintech workflows (onboarding, KYC, support, risk, CRM). Work with product and engineering to ship, evaluate, and improve reliable, secure, cost-effective AI-enabled systems that replace manual processes.

The AI Content Expert is responsible for creating and annotating training data for Large Language Models, ensuring high-quality standards, and collaborating with teams to improve processes.

As a Backend Engineer, you'll design and scale backend systems for AI, transforming unstructured data into structured context, and develop high-performance retrieval systems.

Design rigorous, deterministic advanced mathematics problems and provide complete verified solutions to train and evaluate state-of-the-art AI models. Produce reproducible, well-documented reasoning and, when needed, computational workflows using Python and scientific libraries. Ensure problems target deep mathematical reasoning and are technically precise.

As an AI/ML Engineer, you will develop and optimize machine learning models for mobile apps, collaborating with cross-functional teams to enhance user experiences.