Top Artificial Intelligence Jobs in Berlin

Owns CrowdStrike’s strategic Schwarz Digit and STACKIT partnership across marketplace, distribution, and reseller channels in Germany and Europe. Develops business plans, pipeline targets, KPIs, joint go-to-market programs, and partner enablement strategies. Recruits and grows channel partners, builds executive relationships, drives enterprise opportunities and quota attainment, coordinates cross-functional teams, and supports sovereignty-focused growth initiatives. Requires substantial German channel sales experience, cybersecurity or cloud marketplace knowledge, strong stakeholder management, regular travel, and fluency in German and English.

Leads Pfizer’s enterprise applied AI strategy, architecture, governance, operating model, and transformation efforts. Drives portfolio-level technical decisions, reusable capabilities, standards, and measurable business outcomes. Provides hands-on architecture and code review using modern AI and agent frameworks while leading engineers, contractors, and vendors. Oversees quality, security, performance, spending, and technical direction, mentors technical leaders, and evaluates emerging technologies and industry trends.

Drive pipeline and bookings growth through strategic Global Systems Integrator partnerships across Europe. Develop joint business plans, coordinate enterprise sales pursuits, generate demand, strengthen executive relationships, expand partner-led services and platform adoption, and monitor performance through business reporting. Collaborate with Sales, Marketing, Product, Services, Finance, and alliance teams to execute go-to-market initiatives and deliver measurable revenue outcomes.

Leads an international data science and AI team of up to eight members focused on commercial analytics and AI accelerators. Owns demand intake, prioritization, product strategy, model and data product delivery, and enterprise-scale ML/AI platform development. Partners with commercial, marketing, finance, and brand leaders to translate advanced analytics into business recommendations, revenue growth, and resource optimization. Requires executive communication, team-building, product management, and hands-on expertise in ML, LLMs, agentic workflows, cloud deployment, and pharma or healthcare analytics.

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.

Own product direction and delivery for Affinidi’s Trust Fabric suite, helping build secure AI systems with verifiable identity, policy guardrails, and observability. Partner closely with engineering to define technical solutions, manage trade-offs, deliver iteratively, and improve developer workflows. Shape strategy and roadmaps, resolve ambiguity, align cross-functional stakeholders, and drive products from concept to production.

Manages end-to-end global transparency reporting across EMEA, including data collection, validation, submissions, reconciliations, governance, risk assessments, audit readiness, and remediation. Leads compliance reporting teams, monitors regulatory changes, advises cross-functional stakeholders, and drives process improvements. Oversees reporting systems, automation, analytics, visualization, training, and change management while improving data quality, scalability, and compliance outcomes.

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.

Conduct large-scale molecular dynamics and free energy simulations for protein-ligand and protein-membrane interactions. Build reproducible Python workflows and machine learning-ready scientific datasets using distributed computing infrastructure. Collaborate with computational biologists, machine learning researchers, and engineers to integrate simulation outputs into biomolecular models. Validate results against reference calculations and experimental data, assess uncertainty and convergence, and independently lead research projects producing novel methods, publications, datasets, and software.

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

Own end-to-end product execution for an AI-native B2B enterprise MedTech software platform. Lead and develop 2–3 Product Managers while remaining hands-on in customer discovery, requirements definition, prioritization, engineering refinement, and product delivery across multiple squads. Partner with customers, Engineering, and Design; make product decisions amid ambiguity; improve product operating processes; and help shape AI-first product development.

Designs and maintains product taxonomies, ontologies, navigation structures, metadata, and product attributes across marketplace verticals. Evaluates taxonomy changes with researchers and analysts, documents governance standards and data models, and collaborates with engineering, product, design, data science, legal, localization, and support teams. The role improves listing quality, search relevance, browsing, and item discovery while supporting machine-learning classification systems and marketplace growth.

Own the end-to-end lifecycle, vision, roadmap, KPIs, and business impact of a high-revenue content syndication SaaS product. Expand capabilities beyond video into images, enhanced content, and product information while embedding compliance into workflows. Collaborate with sales, engineering, and customer support to address customer needs, market trends, and business goals. The role requires strong AI knowledge, hands-on execution, data-driven decision-making, and German and English fluency.

Own and build Optiml’s DACH enterprise sales engine by generating pipeline, leading complex multi-stakeholder deals, engaging senior decision-makers, translating AI-driven real estate solutions into business cases, and closing high-value contracts. The role requires structured sales execution, accurate forecasting, strong executive communication, and market insight feedback to product and go-to-market teams.

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.

Design and maintain scalable data pipelines, connectors, and reusable data products to make enterprise data AI-ready. Enable RAG, semantic search, agentic workflows, and production deployment of AI solutions while enforcing data quality, governance, metadata, security, and cross-team collaboration.

Lead AI Value Analyst responsible for building and maintaining business cases for AI initiatives, estimating and tracking benefits, and reporting ROI. Partners with stakeholders, Finance, and AI CoE to quantify productivity, cost, revenue, and risk impacts, prioritize opportunities, validate data and assumptions, and produce dashboards and presentations to communicate realized value and governance across the AI portfolio.

Lead workshops, architect and design Workday Extend applications, deliver requirements and design to developers, manage and guide Extend consultants, liaise with clients and Workday, and support pre-sales and AI-enabled solutioning.

Lead end-to-end implementations of AI-powered ERP automation products, translating customer requirements into scalable solutions and coordinating with engineering teams on integrations. Manage multiple stakeholders and projects, partner with sales on implementation plans, support product adoption, and convert customer feedback into platform improvements. The role requires strong project management, analytical, communication, and problem-solving skills, plus fluent German and English and experience in consulting, technical implementation, process automation, or project management.

Source proprietary company data and domain expertise for frontier AI labs, manage outreach and enterprise relationships, negotiate data-sourcing agreements, and coordinate with internal data and product teams to deliver structured, training-ready datasets. Build and prioritize a pipeline of prospective data sources and enterprise partners.

Manage relationships with AI-native startups, scaleups, and labs in Germany. Understand customer goals, develop AI solution strategies, coordinate NVIDIA technical and business resources, drive adoption of AI platforms, build ecosystem partnerships, develop customer references, identify emerging use cases, and represent NVIDIA at industry events. The role requires deep AI industry knowledge, strategic planning, cross-functional collaboration, and familiarity with NVIDIA’s software, server, and cloud stack.

Design, build, and operate an enterprise AI Hub providing shared runtime, CI/CD, model registry, observability, governance, and developer tooling to enable scalable, secure production AI and self-service capabilities across cloud and hybrid environments.

Design, build, deploy, and optimize production-grade generative AI agents, copilots, and intelligent workflows. Lead end-to-end delivery from solution design and prompt engineering to deployment, monitoring, and continuous improvement. Partner with business stakeholders to transform processes for AI-first execution, define KPIs, ensure governance and security, provide training and change management, and contribute reusable frameworks and best practices across the AI Center of Excellence.

Lead complex global software development and technology transformation projects for Microsoft customers in Germany. Responsibilities include project governance, risk and change management, stakeholder communication, resource allocation, financial oversight, scheduling, cloud adoption, customer-focused delivery, and continuous improvement across cross-functional and partner teams.

Architect and build the AI layer for Neo4j’s Hume Maestro platform. Responsibilities include setting the AI technical roadmap, contributing hands-on to production code, designing scalable AI architectures, establishing model evaluation and deployment practices, integrating AI with front-end and platform systems, and collaborating with Product and Science stakeholders. The role may eventually evolve into leading and mentoring a dedicated AI engineering team.