Top Artificial Intelligence Jobs in Germany

Work directly with the CEO to execute high-priority cross-functional initiatives from planning through completion. Responsibilities include preparing investor, customer, and leadership sessions; coordinating teams and sites; managing multiple workstreams; resolving bottlenecks; and establishing KPIs, dashboards, playbooks, ownership, and progress-tracking processes. The role requires strong analytical, communication, prioritization, and stakeholder-management skills in a fast-growing robotics company.

Analyze and resolve software bugs and security vulnerabilities across complex codebases. Develop and refactor backend applications, conduct penetration testing and security audits, optimize performance, apply secure development practices, document findings, and provide cybersecurity and engineering insights for AI training datasets.

Research and develop GPU-accelerated techniques for AI, deep learning, machine learning, and HPC workloads. Analyze and optimize complex algorithms across CPU and GPU architectures, perform low-level performance tuning, publish optimization techniques, and collaborate with hardware, software, research, and developer communities to influence future architectures and programming models.

Own the discovery, validation, commercialization, and go-to-market launch of new AI and green technology products for renewable installers. Conduct customer research, identify revenue opportunities, test pricing and sales models, and coordinate sales, marketing, technology, and external partners. This is a hands-on, on-site role requiring strong ownership, customer engagement, entrepreneurial initiative, and fluent German and English.

Own go-to-market initiatives for new software products and services, from customer discovery and idea validation through pricing, sales, partnerships, and launch. Engage daily with renewable installers, identify revenue opportunities, test commercial models, and coordinate sales, marketing, technology, and external partners. This is a full-time, on-site Berlin role requiring C2 German and fluent English.

Own post-sale technical delivery for enterprise AI solutions, including workflow analysis, data readiness, AI workflow configuration, integrations, deployment, security approvals, rollout, adoption, and expansion. Partner with customers, founders, Product, and R&D to deliver measurable business value and improve the company’s implementation function.

Design, build, and operate cloud-native infrastructure and platform capabilities for enterprise AI applications. The role focuses on Kubernetes, Docker, CI/CD, Infrastructure-as-Code, observability, security, multi-tenant architecture, secrets management, and reliable production deployments. The engineer collaborates with AI and software teams to move solutions from prototypes to production, contributes platform-related code, supports architecture decisions, and drives automation and operational best practices.

Design, develop, test, and deploy enterprise AI applications, copilots, agents, and intelligent workflows. Translate business needs into scalable AI solutions, integrate enterprise systems and APIs, establish evaluation and monitoring frameworks, and ensure governance, security, auditability, and responsible AI practices. Lead cross-functional initiatives, advise stakeholders, optimize production solutions, and evaluate emerging AI technologies.

Develop and operate HARMAN’s enterprise AI platform, including platform services, AI applications, agents, integrations, MLOps and LLMOps workflows. Responsibilities include model deployment and lifecycle management, CI/CD automation, infrastructure-as-code, security, governance, observability, monitoring, troubleshooting, performance optimization, testing, and technical documentation. The role partners with architects, product owners, security teams, data engineers, and application developers to deliver scalable, reliable, and governed AI capabilities.

Build and lead the company’s first legal function across German and US corporate governance, commercial contracts, export controls, sanctions, cybersecurity and product compliance, IP, funding obligations, employment, GDPR, and open-source licensing. Establish templates, approval frameworks, signing authority, decision rights, and legal processes that support international hardware commercialization. Manage external counsel, legal budgets, and specialist escalation while advising leadership on corporate and regulatory matters.

Develop and integrate AI solutions for space systems, including predictive maintenance, anomaly detection, autonomous orbital decisions, and ML-based signal processing. Design, implement, verify, and validate embedded real-time flight and simulation software in C. Integrate AI models with hardware, analyze requirements, troubleshoot complex systems, automate development and testing, maintain technical documentation, and support agile processes and relevant aerospace standards.

Leads AI and experience orchestration sales initiatives, serving as a subject matter expert for account teams and enterprise customers. Responsibilities include shaping deal strategy, territory planning, pipeline development, forecasting, customer workshops, AI use-case prioritization, proofs of concept, proposals, pricing, presentations, and sales enablement. Partners cross-functionally with marketing, product, customer success, and professional services while influencing senior stakeholders and driving AI-powered customer experience opportunities.

Leads the Edge AI team and roadmap from research through production deployment. Responsibilities include hiring and mentoring engineers, optimizing and deploying models on embedded accelerators, managing model export and inference toolchains, partnering with hardware, software, and product teams, benchmarking performance, and debugging accuracy, latency, power, and memory issues.

Owns an AI-focused financial product vertical from strategy through launch, including roadmap, backlog, metrics, technical design, money-movement correctness, reliability, security, and scalability. Incorporates regulatory requirements such as KYC, sanctions screening, transaction monitoring, privacy, and data residency. Defines responsible AI usage, evaluation, human oversight, and failure handling while coordinating Engineering, Design, Compliance, Operations, Treasury, and Finance.

Lead technical presales for complex enterprise AI and contact center opportunities across Eastern Europe and DACH. Responsibilities include discovery, solution design, customized demonstrations, presentations, proof-of-concepts, competitive analysis, and translating AI capabilities into business value. The role also involves thought leadership at customer events, collaboration with sales and product teams, and shaping solutions for major enterprise deals. Fluency in English and Polish, Germany-based work, and regional travel are required.

Lead product direction, roadmaps, standards, metrics, and execution for major areas of KIRA’s AI Investing App. Guide PMs, product owners, designers, and engineers across multiple squads while balancing UX, data, engineering, regulatory, operational, and business constraints. Drive launch quality, post-launch learning, and continuous improvement across financial products including investing, payments, savings, insurance, and travel.

The Senior Solutions Engineer collaborates with customers to design and sell innovative internet solutions, manage technical queries, and support internal teams, focusing on cloud and security technologies.

Own product areas for KIRA’s AI stockbroking and financial-services applications. Define user problems, product strategy, scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial workflows; launch features; monitor performance; and continuously iterate using data, research, feedback, and production insights.

Participate in Veeva’s Consultant Development Program, learning to configure cloud software and AI solutions for Life Sciences customers. Lead discovery workshops, gather requirements, design workflows, tailor platform configurations, translate business needs into technical specifications, manage implementation scope and milestones, and guide customers through deployment using best practices.

Lead engineering execution and technical direction while remaining approximately 75% hands-on. Responsibilities include developing LLM- and AI-powered products, coding, code review, debugging, platform performance, sprint planning, cross-functional coordination, technical mentorship, recruiting, and supporting engineers’ growth. The role partners closely with founders and product teams and offers a path toward Engineering Manager responsibilities.

Lead complex enterprise customer engagements as the senior technical authority for data and AI strategy. Drive Databricks adoption, consumption, competitive displacement, and revenue growth through architecture, migrations, streaming systems, lakehouse platforms, and AI/ML solutions. Manage executive relationships, orchestrate cross-functional teams, mentor solutions architects, develop competitive strategies, and contribute to technical thought leadership. Weekly travel is required.

Own AI Investing product areas from user research and problem definition through roadmap planning, launch, measurement, and iteration. Partner with engineering, design, data, operations, compliance, and business teams to simplify financial products, make informed trade-offs, and deliver customer-focused features quickly. Use metrics, feedback, experiments, and production insights to improve outcomes across insurance, payments, savings, investing, travel, and related financial services.

Own relationships with 40–50 enterprise EMEA clients, leading onboarding, product adoption, usage monitoring, renewals, and account expansion. Help build scalable customer success playbooks, manage NRR and GRR KPIs, and contribute to team OKRs. The role requires demonstrating value for technical SaaS products, navigating complex stakeholder environments, solving customer challenges, and driving commercial outcomes.

Leads the creation and delivery of learning programs across multiple sites, including sales enablement, onboarding, agent development, and leadership training. Partners with country L&D managers and stakeholders to improve learning engagement, reduce early employee turnover, implement post-workshop materials, and develop local career frameworks. Supports AI integration into learning journeys and travels to other offices as needed.

Manage learning and development initiatives across multiple sites, including sales enablement, onboarding, agent development, leadership training, and learning-platform engagement. The role facilitates workshops, creates local development frameworks, improves training materials and customer-facing tools, supports employee retention, and helps deploy AI solutions within learning programs. It also partners with country L&D managers and internal stakeholders and travels to other offices as needed.