Top Artificial Intelligence Jobs in Berlin

The Chief of Staff will support the CEO in executing company strategy, managing financial operations, applying AI to improve processes, and leading high-impact projects across the organization.

Provide technical support for ClickHouse and Langfuse customers across EMEA and global regions through cases, chat, Slack, community channels, and calls. Troubleshoot database, cloud infrastructure, AI application, tracing, and evaluation issues within SLA and on-call rotations. Develop documentation and educational content, assist with technical proofs of concept, mentor colleagues, escalate bugs, collaborate with Engineering and Product teams, and support customer implementations directly in codebases.

Own and build the data ecosystem: design pipelines from customer systems (HubSpot, Aircall), implement AI-driven workflows and predictive models, create BI dashboards, and partner with Sales/Marketing to operationalize data-driven revenue processes. Hands-on engineering in Python/TypeScript and n8n to deploy end-to-end solutions.

Develop and optimize GPU- and CPU-accelerated numerical software libraries for AI, analytics, image processing, computer vision, and scientific simulation workflows. Responsibilities include designing scalable algorithms, performance tuning, benchmarking across architectures, collaborating on feature requirements and technical roadmaps, providing technical leadership, and improving library usability and performance.

Designs end-to-end enterprise AI architectures on AWS, including LLM orchestration, integrations, cloud infrastructure, security, scalability, and governance. Leads technical discovery workshops, creates architecture documentation and standards, guides engineering squads, reviews designs, presents decisions to senior stakeholders, and evaluates third-party AI platforms for buy-versus-build decisions. Requires extensive senior architecture experience and fluent Dutch and English.

Own the technical presales strategy for complex enterprise deals across DACH and expansion markets. Lead discovery, technical deep dives, customized demonstrations, solution design, POCs, and POVs. Translate AI Agent and contact center technologies into business value for senior stakeholders, provide competitive analysis, and collaborate with product teams. Represent NiCE Cognigy through events, webinars, trade shows, and thought leadership while supporting internal enablement and customer feedback.

As a Senior Machine Learning Engineer, you will develop and scale customer-facing AI models, ensuring quality integration with business solutions, and mentoring peers.

Lead Project & Program Manager drives strategic initiatives for Libra from concept to execution, leading cross-functional teams to deliver market expansion, operational scaling, and commercial programs. Responsibilities include program planning, governance, budget and KPI tracking, risk management, stakeholder alignment, change management, and go-to-market readiness across regions.

Build and own end-to-end features for Chainguard's AI-enabled CI/CD and supply-chain security products. Design, implement, and iterate on integrations like hardened GitHub Actions, container tooling, and agentic AI features. Drive architectural decisions, collaborate with Product and front-end teams, and ship secure, production-ready developer tools.

Leads NVIDIA’s AI Physics sales strategy across EMEA, driving market growth, strategic customer adoption, ecosystem partnerships, pipeline development, and production-scale success across engineering-intensive industries. Builds executive relationships, identifies high-value use cases, communicates market insights internally, and promotes AI Physics, simulation, digital twin, and accelerated computing solutions.

Owns NVIDIA’s EMEA go-to-market motion for its Agentic AI Platform, driving customer and partner adoption across enterprise, cloud, public sector, defense, and regulated environments. Translates complex AI, security, licensing, legal, and deployment requirements into sales plays, reference architectures, field guidance, workshops, and executive content. Coordinates product, engineering, legal, security, sales, and ecosystem teams while sharing market requirements and connecting technical adoption to revenue outcomes.

Design and build agentic conversational systems combining LLMs, reasoning components, and data pipelines. Lead ML/NLP model training, evaluation, optimization, deployment, and experimentation. Integrate intelligent agents into recruiting workflows, mentor engineers, and improve reliability, personalization, and observability of production ML systems.

Build and own end-to-end customer-facing features and APIs, maintain web app security and performance, and develop scalable multi-modal ingestion pipelines. Model the construction ontology and project graph, implement entity resolution, integrate with customer systems, and contribute to workflow/platform abstractions, evaluation tooling, and human review surfaces to support auditable, evidence-linked AI outputs.

Lead end-to-end implementations of QVAC-powered AI deployments, coordinating clients, engineering, product, and legal teams; define roadmaps, manage risks, track progress, and ensure production rollout while aligning technical capabilities with business requirements.

The Sales Development Representative will identify potential manufacturing customers, initiate conversations, qualify leads, and work closely with Account Executives to enhance sales pipeline and strategies.

Drive solution sales for Microsoft Cloud and AI within Automotive and Manufacturing enterprise accounts. Qualify opportunities, build stakeholder relationships, orchestrate deals with partners and consulting teams, align AI/cloud strategies to business outcomes, use analytics to prioritize pipeline, and support secure AI transformation and customer success.

The Backend Engineer will develop and maintain features for Restream web services, design backend APIs, ensure infrastructure resilience, and contribute to a collaborative team environment.

Lead end-to-end AI agent product development for Sales and Marketing: define roadmap, own backlog, drive discovery-to-adoption, lead engineers, partner with UX, and ensure secure, scalable production deployments.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Lead end-to-end partner digital journey and define strategy for a central AI platform. Drive LLM orchestration, agentic workflows, RAG patterns, API integrations, partner design system ownership, cross-functional alignment, and mentor product colleagues.

Lead the design, build, and deployment of AI-powered agents, workflows, and integrations for global marketing. Evaluate buy-vs-build, integrate platforms (HubSpot, Salesforce, Meta, Google, LinkedIn), optimize AI economics, and measure ROI while collaborating with marketing teams to automate and improve campaign execution and content localization.

Build, deploy and maintain purpose-built AI agents and LLM integrations for product processes. Connect data sources, design prompts, validate outputs, and ensure reliability and scalability of automations and shared tooling for the product team.

Lead and grow a new AI Engineering and AI Platform team to productionize AI use cases. Provide technical direction for cloud-native backend systems, LLM API integrations, agentic workflows, IaC, CI/CD, observability, governance, and cost management while collaborating with Data Science, Product, Security and stakeholders.

Lead the AI function, define roadmap, and build production generative AI systems (voice, chat, document). Split time between hands-on engineering (~40%) and leading the AI team, establishing RAG/agentic workflows, evaluation, observability, and best practices. Collaborate with product and engineering to deliver reliable, user-focused AI features.

Seeking a Senior Full-Stack Engineer to develop AI-driven web and mobile applications, focusing on scalable architectures and API integrations. Collaborate with product teams to translate features into technical solutions.