Top Artificial Intelligence Jobs in Berlin

Lead the commercial development and operating performance of a two-sided automotive marketplace connecting private vehicle sellers with professional partners. Own growth, revenue, margin, unit economics, customer and partner experience, performance metrics, and operational quality. Coordinate Product, Technology, Operations, Analytics, Sales, and Finance teams, translate strategy into execution, and communicate data-backed decisions to senior leadership.

Own enterprise customers’ AI adoption roadmaps from deployment through expansion. Partner with executives to define AI strategies, coordinate Product, Services, Sales, Success, and partners, and guide solution design and technical escalations. Track adoption, automated resolution, retention, and expansion metrics to drive measurable outcomes. Advise on responsible AI, data governance, compliance, and sustainable implementation while leading success planning, stakeholder alignment, and renewal-focused engagements.

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.

Lead and mentor a team of Applied Scientists and AI/ML Engineers to design and deliver production-grade AI solutions across structured CRM and unstructured data. Drive technical strategy for agentic workflows, RAG/vector DB systems, and real-time reasoning. Partner with AI Platform on LLMOps and cloud infrastructure, act as a technical authority, and contribute as a high-impact individual contributor to ship customer-focused AI products.

Own the full sales cycle for Slack across a high-velocity mid-market account portfolio. Responsibilities include pipeline generation, prospecting, discovery, AI-focused product demonstrations, business-case development, forecasting, negotiation, and closing. The role partners with Salesforce account executives, solution engineers, customer success teams, and partners to drive new-logo and expansion opportunities, demonstrate ROI, and build long-term customer relationships.

Guide prospective customers through Camunda evaluations by mapping requirements to solutions, demonstrating product value, conducting technical Q&A, and developing evaluation plans. Partner with Account Executives and Solution Architects to qualify opportunities, execute presales engagements, support RFI/RFP responses, create technical content, implement code snippets, and drive product wins through consultative selling.

Partner with HR teams to analyze hire-to-retire processes, define technical requirements, and deliver scalable HR technology, automation, and AI solutions. Build Claude-based applications, n8n and UiPath workflows, Python automations, integrations, and secure HRIS-connected tools. Lead initiatives through design, testing, implementation, and go-live while improving Workday, Jira service desks, HR workflows, security models, payroll transformations, and employee experiences.

The Customer Success Manager (SEO) will onboard clients, advise on SEO strategies, review performance, and collaborate with teams to enhance customer enablement.

Designs and delivers AI-native solutions across business functions including People, Legal, Finance, and Operations. Responsibilities include identifying transformation opportunities, building and deploying AI agents and automated workflows, integrating enterprise systems, driving adoption, measuring business impact, applying governance and human oversight, and mentoring colleagues. The role partners with functional leaders to redesign operating models and continuously improve production AI solutions.

Own and expand a strategic EMEA partnership, driving joint business planning, pipeline creation, revenue growth, executive alignment, go-to-market execution, partner enablement, and cross-functional collaboration. The role requires managing complex enterprise software alliances, influencing internal and partner teams, developing joint solutions and campaigns, and delivering measurable commercial outcomes across regional markets.

Serve as a senior pharmacovigilance domain expert bridging case-processing operations, product strategy, and AI automation. Guide safety workflow design, evaluate AI outputs, define future PV operating models, engage early-adopter customers, and create complex scenarios for platform stress testing. Collaborate with product, engineering, and executive customer teams to ensure accurate, compliant, and effective safety automation.

Serve as a technical advisor for digital-native and startup customers, leading discovery, cloud and AI architecture, demonstrations, workshops, proofs of concept, and production-readiness engagements. Translate business goals into Azure solution plans, remove technical blockers, influence technical decision-makers, and accelerate Azure adoption and consumption. Partner with account teams, specialists, customer success, engineering, and product teams to advance opportunities, create reusable technical patterns, and support complex customer sales motions.

Review and annotate short video and audio clips for AI training and evaluation. Assess AI-generated descriptions for accuracy, relevance, and appropriateness; flag potentially inappropriate or ambiguous content; provide concise feedback; and maintain consistent annotation quality while following confidentiality, data protection, and moderation guidelines in a remote environment.

Leads NVIDIA’s EMEA public-sector AI business development strategy, collaborating with sales, marketing, solution architects, developer relations, and partners. Responsibilities include sales enablement, account planning, pipeline and revenue growth, customer engagement, opportunity reviews, government lighthouse-account development, partner coordination, case studies, and AI platform adoption. The role also mentors developer relations teams and communicates technical AI value to government customers and stakeholders.

Build and lead n8n’s internal AI and automation enablement function. Run recurring workshops, office hours, build-alongs, bounty hunts, hackathons, and dogfooding initiatives for technical and non-technical teams. Develop reusable templates, measure AI fluency and adoption, support cross-functional champions, and act as product owner for a safe internal automation playground. Partner with IT, Security, Data, and Solutions Engineering to define access, credential, and environment requirements.

Build AI-powered learning resources, automated workflows, onboarding experiences, and knowledge systems. The role involves prototyping Claude-supported solutions, maintaining Sana LMS and Notion, automating enrollment and reporting, creating learning content, and partnering with stakeholders to solve learning needs in a remote, async-first environment.

Build and deploy production generative AI systems, including RAG pipelines, agentic workflows, document understanding, document generation, and conversational interfaces. Own AI architecture, implementation, evaluation, testing, observability, and deployment while collaborating with product, design, and engineering teams to deliver reliable user-facing functionality for legal technology products.

Develop and deploy scalable, production-grade machine learning and AI solutions for financial research. Build LLM- and NLP-based applications, collaborate with senior engineers, and contribute to reliable AI-driven products. Responsibilities require Python, software engineering, deep learning, databases, Docker, and at least one major deep learning framework. Preferred experience includes RAG pipelines, vector databases, LLM fine-tuning, cloud platforms, and Kaggle competitions.

Lead design and build of an end-to-end AI contract-review agent: prompt orchestration, RAG pipelines, fine-tuning, web UI and tooling, data/model infra, deployment (CI/CD/cloud), and product-driven features like assumption mapping and contract diagnostics.

Drive enterprise revenue by owning complex €100k+ sales from discovery through contract signature. Build pipeline through outbound prospecting, navigate multi-stakeholder buying committees, develop ROI-based business cases, manage procurement, security, legal, and negotiations, and close new ARR. The role requires strong executive relationships, strategic account planning, quota ownership, enterprise sales experience, business-level German and English, and on-site work in Berlin five days per week.

Evaluate AI-generated customer service and technical responses for clarity, usefulness, natural language, technical accuracy, JSON validity, formatting, and guideline adherence. Provide clear feedback explaining evaluation decisions. The role requires multilingual fluency, coding knowledge, strong written communication, attention to detail, and consistent judgment. Experience with AI evaluation, quality assurance, APIs, structured data, customer service, software development, or technical writing is preferred.

Lead the company’s AI function by defining strategy, managing and mentoring the AI team, and building production-ready generative AI systems across voice, chat, and document products. Design agentic workflows, RAG and LLM architectures; establish evaluation, testing, monitoring, and observability practices; and contribute hands-on to implementation. Partner with product and engineering teams to translate AI capabilities into reliable, valuable user features.

Create and evaluate game development challenges for AI training. Build small game projects, introduce and resolve gameplay bugs, design multi-system features, write task briefs and acceptance criteria, develop verified reference solutions, and conduct end-to-end playtesting. Candidates must demonstrate hands-on experience with a major game engine, relevant programming or scripting technologies, gameplay debugging, interactive feature design, technical documentation, and a verifiable game development portfolio.

Design and evaluate challenging mobile software engineering tasks for AI systems. Responsibilities include creating debugging, feature development, refactoring, state management, lifecycle, and performance tasks; building reproducible environments; writing deterministic automated tests and verifiers; developing reference solutions; and documenting rigorous evaluation criteria.

Designs and demonstrates enterprise-ready agentic AI architectures using NVIDIA technologies. Leads technical discovery, builds proofs of concept, develops reference architectures, optimizes inference and workloads, and supports secure deployment across local, on-premises, hybrid, sovereign, and cloud environments. Partners with customers to integrate orchestration, retrieval, model serving, sandboxing, governance, and GPU infrastructure while creating reusable playbooks, benchmarks, workshops, and enablement assets.