Top Artificial Intelligence Jobs in Germany

Design and implement backend business logic and orchestration for AI coding agents, integrate agents with product surfaces, external APIs and CLIs, build highly concurrent asynchronous workflows, improve context handling and failure recovery, collaborate with product and ML teams, and own technical design and code quality.

Develop and maintain full stack applications, integrate AI capabilities using APIs, and collaborate with stakeholders to enhance workflows.

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 end-to-end organic growth programs for B2B tech clients, owning strategy, execution, deliverable quality, renewals, and commercial-impact metrics across a portfolio of up to ten accounts. Prioritize work, set and keep commitments, evaluate recommendations, and partner with a production team that executes briefs, decks, and data.

Lead product vision and roadmap for AI-native R&D tools in materials science. Drive discovery, validation, and delivery of AI features by coordinating data scientists, engineers, chemists, and vendors; perform user research, define requirements, manage backlog, and measure adoption and ROI to scale impactful AI solutions.

Design, implement, and deploy AI solutions using LLMs, RAG, and AI agents. Identify AI use cases, evaluate risks and limitations, support digital and data strategy, and collaborate with teams to deliver production-ready solutions.

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.

As an AI Product Manager, you will define the product roadmap, collaborate with teams to launch AI features, and drive data-driven decisions.

As an AI Automations Engineer, you will design and build tooling for GTM, Operations, and Finance teams, automating processes and enhancing systems with a focus on AI.

Lead Data & AI consulting engagements from strategy to delivery: identify high-impact use cases, define roadmaps, guide bespoke AI and platform development, manage stakeholders and project delivery, support sales and proposals, and create reusable assets while representing the discipline externally.

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.

Work as an intern building software and AI application features for production manufacturing systems. Collaborate with senior engineers to troubleshoot, document, and ship solutions, integrate the platform into customer environments, and translate customer requirements into technical implementations while learning production processes, IT infrastructure, and AI product deployment.

Join the AI Engineering team to design, build, deploy, and scale production AI systems. Translate business problems into AI solutions, industrialize ML models, design AI pipelines and platforms, ensure performance and monitoring, and drive MLOps best practices across architecture and governance.

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.

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.

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.

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.

Develop and optimize real-time, high-throughput signal processing on embedded GPU modules: implement parallel GPU kernels (FFT, filtering, detection), design zero-copy DMA ingest paths, build deterministic streaming pipelines, evaluate vendor SDKs, maintain board support and OS images, and validate performance with profiling, numerical/bit-true tests and CI integration. Collaborate in an interdisciplinary prototyping team and support integration/measurement campaigns.

Develop application/control layer for sensor demonstrators: design interfaces, implement mode/resource/config management, ensure operability, observability and testability (scheduling, health monitoring, data recording, operator API). Participate in prototyping, automated testing and CI/CD, and integration/measurement campaigns.

Lead EMEA go-to-market for Physical AI by sourcing executive-level pipeline, accelerating top accounts, building EMEA-specific playbooks, enabling regional sales, and converting lighthouse wins into sustained cloud consumption across robotics, autonomy, simulation, and related AI-native industries.

Lead enmacc's transition to an AI-first trading platform by developing AI solutions and predictive models tailored for energy trading, overseeing a unified Data & AI team, and driving product innovation.

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.