Top Artificial Intelligence Jobs in Germany

Lead Andercore’s European M&A and roll-up strategy from target origination through closing. Build acquisition pipelines, market maps, valuation models, investment cases, deal structures, and due diligence processes. Partner with technology and operating teams to quantify AI-driven value creation, develop integration plans, and track portfolio performance. Establish the company’s repeatable M&A infrastructure and eventually build a Corporate Development team.

Owns Splunk’s global strategic account relationship with SAP, including account strategy, renewals, pipeline development, expansion, enterprise negotiations, forecasting, and long-term customer value. Builds executive relationships, leads international virtual teams across Splunk and Cisco, develops multi-year opportunities, positions security and observability solutions, drives adoption, and aligns customer priorities with commercial outcomes.

Work with strategic customers to design, prototype, and implement AI solutions on the Celonis Process Intelligence platform. Translate business needs into technical solutions (SQL, PQL, Python), build prototypes using generative AI and ML tools, present value to executives, ensure adoption and measurable ROI, and contribute reusable best practices to the Value Engineering Center of Excellence.

Design and productionize ML systems for advertising using multimodal data (image, video, audio, text, structured). Improve MLOps and data platforms, build scalable data pipelines, monitor models, collaborate cross-functionally, and drive team processes and product impact.

Conduct industry-focused AI research on autonomous agents and world models. Develop models involving large language models, active inference, and optimal policies, including architecture experimentation, fine-tuning, deep-learning agent development, and action optimization. Candidates will work on real-world enterprise problems while pursuing cutting-edge research during a fixed-term three- or six-month fellowship.

Build foundational systems for AI models across data modalities, develop agentic systems and specialized models, and implement reinforcement learning and active inference solutions. The role involves hands-on architecture and product development, requiring Python backend expertise, cloud deployment knowledge, DevOps practices, and the ability to contribute across the technical stack in an early-stage startup.

Leads global commercial customer data governance, Customer 360 strategy, segmentation, data quality, reporting, and insight initiatives. Owns customer definitions and hierarchies across SAP and Salesforce, establishes governance and KPI standards, and aligns reporting and analytics investments with business value. Partners cross-functionally to improve data quality, reporting adoption, forecast accuracy, and AI readiness while driving change management and value realization across the commercial organization.

Own the end-to-end architecture for an EMAT flow sensor spanning hardware, embedded software, AI, signal processing, and cloud applications. Guide cross-functional development teams, translate product and customer requirements into technical specifications, ensure regulatory compliance, and lead system integration and testing. Serve as a technical contact for customers and stakeholders while supporting agile collaboration across international teams.

Lead GTM operations across EMEA and APAC by developing commercial growth strategies, forecasting frameworks, territory plans, sales methodologies, dashboards, and pipeline management processes. Partner with executive leaders across Sales, Finance, Marketing, Customer Success, and Partnerships. Use Salesforce, Outreach, Snowflake, AI, and machine learning to improve forecast accuracy, pipeline conversion, reporting automation, and sales productivity.

Serves as a technical trusted advisor for strategic healthcare customers throughout the sales cycle. Responsibilities include advising on interoperability, data platforms, cloud and API architectures, analytics, AI, and GenAI; delivering executive briefings, architecture workshops, demonstrations, solution concepts, and proof-of-concepts; and supporting digital transformation initiatives. The role collaborates with sales, product management, architecture, engineering, and professional services teams.

Lead enterprise solution architecture for strategic Celonis deployments across multiple clients. Design scalable architectures integrating process intelligence, data, automation, and AI; define AI-agent workflows, validation standards, and reusable delivery patterns. Advise executive stakeholders, support pre-sales, guide complex implementations, mentor deployment teams, establish architectural standards, and translate customer process challenges into measurable transformation outcomes.

Architect and implement agentic AI solutions for semiconductor applications, including multi-agent systems, reasoning, planning, and reinforcement learning workflows. Collaborate with hardware, software, and data teams to deploy scalable, usable AI applications. Evaluate emerging agent-based AI technologies and apply them to semiconductor manufacturing challenges. The role also involves AI/ML development, web front-end integration, cloud platforms, MLOps, and continuous adaptation to evolving technologies.

Lead enterprise Celonis implementations by translating business needs into data models, process analyses, KPIs, dashboards, automation, and operational solutions. Direct AI agents, validate outputs, configure the Celonis platform, lead discovery and value workshops, quantify impact, manage delivery outcomes, train users, and support adoption. Apply expertise in enterprise processes, ERP systems, and financial metrics while developing scalable solution patterns and maintaining customer relationships. The role requires consulting leadership, technical fluency, English and German proficiency, and travel up to 50%.

Supports customer projects from planning through implementation, including onsite assistance, system configuration, implementation, and testing. Advances internal automation and AI initiatives, develops project standards and templates, optimizes processes, and converts customer feedback into product insights. The role offers hands-on responsibility in Industrial IoT and Industry 4.0 projects, with at least two Munich office days weekly and occasional customer travel.

Own university and early-career recruiting for the Belgrade site, including school strategy, campus partnerships, sourcing, screening, interview coordination, offers, and closing. Build intern, co-op, and new-grad pipelines; partner with engineering managers to define candidate profiles and hiring standards; maintain ATS discipline; analyze funnel data; and improve recruiting processes and candidate experience.

Designs, builds, operationalizes, and maintains enterprise-scale data applications and scalable ETL/ELT workflows. Develops systems for collecting, ingesting, storing, processing, modeling, warehousing, and retrieving structured and unstructured data. Integrates Generative AI, LLM-based workflows, and agentic automation into secure mission systems supporting Intelligence Community objectives. Collaborates with data scientists, analysts, software developers, and stakeholders in Agile environments.

Lead AI transformation across Sales, Marketing, Customer Success, Partnerships, and Revenue Operations. Identify high-value opportunities, design and deploy production AI agents, agentic workflows, automations, integrations, and enterprise solutions, then drive adoption and measure business impact. Partner with functional leaders, make sound decisions about AI suitability, redesign operating models, improve reliability and governance, and mentor colleagues while establishing reusable standards across the organization.

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.

Design, build, deploy, and operate AI agents, multi-agent systems, LLM services, transformer models, and RAG pipelines for enterprise SaaS products. Own AI solutions end to end, including experimentation, model selection, fine-tuning, deployment, monitoring, scalability, optimization, and production operations. Apply AI to search, entity resolution, information extraction, and document understanding.

Own product marketing for Cyara’s Agentic AI assurance products, including positioning, messaging, go-to-market launches, competitive intelligence, sales enablement, technical content, and cross-functional collaboration. The role targets enterprise buyers through sales-led motions and requires measurable pipeline impact, strong writing and presentation skills, and comfort working with technical teams. Experience in AI, contact centers, QA, testing, observability, or monitoring is advantageous.

Develops thermodynamics-based and AI/ML-enabled models for pharmaceutical formulation and process development. Responsibilities include predicting solubility, phase behavior, crystallization, stability, material compatibility, and process performance; integrating mechanistic and experimental data; validating models; assessing uncertainty; creating decision-support tools; and communicating actionable insights to multidisciplinary stakeholders. Requires a PhD-level background and strong expertise in thermodynamics, quantitative modeling, physicochemical data analysis, and scientifically interpretable AI/ML methods.

Drive enterprise sales of Microsoft Cloud and AI solutions for automotive and manufacturing customers. Qualify opportunities, develop sales strategies, manage pipelines, forecast results, and orchestrate cross-functional teams and partners. Engage senior customer stakeholders, align transformation initiatives with business outcomes, support co-selling and customer success plans, and guide secure AI adoption. The role requires technology solution sales experience and fluency in German and English.

Lead product direction and execution for major areas of BJAK's AI Neobank app. Define roadmap, priorities, standards and success metrics across multiple squads; guide PMs, designers and engineers; translate regulatory and operational constraints into product decisions; drive launch quality, post-launch learning and continuous improvement; work across insurance, payments, savings, investing and travel.

Deploys and supports AI edge systems at industrial customer sites. Responsibilities include installing cameras, compute nodes, networking equipment, and hardware cabinets; configuring devices; validating connectivity and edge-to-cloud data flow; automating installation and diagnostics with scripts; troubleshooting hardware, network, and software issues; coordinating logistics; and ensuring reliable, safe, high-performance installations.

Own customer onboarding outcomes by executing and improving onboarding cycles, validating data quality, documenting edge cases, tracking success metrics, and communicating progress and blockers. The role coordinates with installation teams to ensure reliable camera setups and consistent results, while improving checklists, documentation, templates, processes, and tools. Candidates should be detail-oriented, metrics-minded, technically comfortable, and experienced in structured execution roles such as implementation, QA, solutions engineering, operations, or data operations.