Top Artificial Intelligence Jobs in Germany

Drive end-to-end GPU + networking reference architectures and pre-sales integration for NVIDIA AI Cloud Partners. Lead technical account engagements, POCs, performance troubleshooting, roadmap presentations, and project management for complex datacenter networking deployments.

Advise clients on enterprise AI and data strategy, define AI operating models and platform blueprints, assess AI maturity, build business cases and roadmaps, embed Responsible AI, identify people/process/technology needs, and lead workstreams to commercialize AI-driven products and transformations.

Advise clients on creating and capturing value from AI and data by defining AI/data strategy, building value cases and roadmaps, shaping operating models and platforms, embedding Responsible AI, leading large-scale delivery, engaging senior stakeholders, and linking AI initiatives to measurable business outcomes.

Lead end-to-end process transformation for an industry or function, embedding AI agent design into future-state processes. Run client discovery workshops, benchmark and assess change impact, design operating models and adoption plans, coach junior practitioners, contribute to proposals, and document playbooks. Specify AI agent autonomy, escalation triggers, and human-agent handoffs across process steps.

Design AI-integrated future-state processes and AX (agent experience) interactions, perform benchmarking and trend analyses, build data-driven frameworks and visualizations with AI tools, assess change impacts, and support delivery of digital and platform solutions across operations within a consulting context.

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.

Lead development and governance of a centralized catalog of reusable AI components (prompts, agents, templates, RAG patterns). Define standards, manage lifecycle (intake, tagging, publishing, deprecation), ensure compliance with infrastructure and security, collaborate with engineers to productize reusable assets, monitor usage and impact, and support enterprise AI best practices and adoption.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Provide legal advice on digital, AI, cloud, software licensing, data protection and cyber law for robotics business. Draft, review and negotiate global technology agreements, support digital transformation compliance, monitor regulatory trends, collaborate with global legal teams, and train stakeholders on legal and ethical standards.

Design and operate an AI-native gameplay analytics ecosystem: define tracking, storage, processing, and semantic layers; build AI-driven reporting and agentic workflows; ensure data correctness; generate product intelligence and set organization-wide agent standards.

Create end-to-end game and marketing assets using AI-assisted workflows. Build and maintain ComfyUI pipelines, combine AI outputs with Illustrator/Photoshop/After Effects, animate assets, ensure visual consistency with the Empire style, test and integrate new AI tools, and collaborate with art, product, CRM, design, and development teams.

Lead AI governance across the model lifecycle: build scalable governance platforms, define controls for agentic AI, translate laws (e.g., EU AI Act) into actionable processes, partner with engineers and compliance, and improve AI risk management and auditability.

Act as the technical bridge between AI/analytics capabilities, customers, and sales across EMEA. Identify use cases, run discovery workshops, demos, pilots and PoCs, enable sales via content and training, feed product/R&D with field insights, and support product launches. Role requires regular travel across EMEA and close collaboration with HQ.

Deploy and integrate ICEYE's intelligence platform into secure, often air-gapped environments; build containerized deployments, RAG and LLM-based AI workflows, data-fusion pipelines combining SAR and other intel, and lightweight analyst tools. Work embedded with customers to prototype, train, and iterate solutions while troubleshooting disconnected deployments.

Lead architecture and implementation of the AI-first backend and agent platform. Build scalable Python services (FastAPI), design APIs, own semantic data layer (Postgres, dbt, pipelines, caching), integrate LLMs/agents (RAG, function calling, guardrails), set standards for observability and reliability, prototype rapidly with product and FDEs, mentor engineers, and drive technical direction and adoption metrics.

Build and ship production-grade AI backend features (RAG, retrieval, LLM integrations, agentic workflows), implement necessary frontend changes, design evaluation and observability for LLM systems, collaborate with Product and DevOps, and scout new AI technologies for deployment in an industrial B2B SaaS context.

Design, implement, and ship backend AI features (RAG pipelines, retrieval, agentic workflows, LLM integrations). Build production REST APIs, evaluation/observability for LLM features, collaborate with Product and DevOps, and translate research into production-ready solutions.

Build and evolve backend and AI systems for MAIA: implement production-grade features, RAG pipelines, retrieval strategies, and LLM integrations; create evaluation and observability for non-deterministic systems; collaborate with Product, DevOps, and customer teams; drive engineering standards and technical direction as a senior engineer.

Develop intelligent agents for a materials discovery engine, orchestrating scientific workflows and integrating experimental design for sustainability solutions.

Lead and own Agent0: co-own roadmap with Product, hire and grow a senior AI engineering team, drive delivery of production-grade agentic AI, set evaluation and monitoring standards, prototype innovations, and provide thought leadership on AI production excellence.

Design and implement execution primitives for AI/agent workflows in Kestra's Java core, build and maintain plugins to connect LLM providers and agent frameworks, convert agent use cases into reusable blueprints with product, and ensure AI executions are observable, debuggable, correct, and reliable.

Build end-to-end AI features and prototypes across backend and frontend, prototype AI agent use cases, create UI/blueprints/examples to make AI workflows usable, and ship features quickly in collaboration with product and backend teams.

Own AI workflows product: discover and validate AI use cases with customers, define roadmap and specs, create reusable blueprints with engineering, and prioritize what not to build.

Lead design, development, and deployment of AI/ML models and pipelines to support combatant command operations. Build scalable data and model architectures, integrate multi-source data, apply predictive, NLP, clustering, and network techniques, and operationalize explainable models and decision-support tools for mission-driven analytics and campaign assessment.

Design, build, and run production agentic workflows and reusable components for delivery processes. Implement RAG-backed knowledge bases, monitoring, evals, observability, and human-in-the-loop feedback to improve agents and integrate them with delivery teams and business tools.