Top Artificial Intelligence Jobs in Cologne

Lead full-cycle enterprise sales for an Energy AI platform: engage C-level and technical stakeholders, build data-driven pipeline, refine GTM and sales playbook, run demos, negotiate and close high-value deals, provide customer feedback to Product/Engineering, and use modern tech/automations to scale revenue.

Design, build, deploy and maintain agentic AI systems and automated workflows for Sales, AM and CSM. Implement autonomous data orchestration, signal-based data architecture, and forecasting pipelines. Integrate agents with CRM (Salesforce/HubSpot) and BI, monitor performance, implement guardrails, and collaborate with PlatformOps, Engineering, Data and Process teams.

Lead EMEA go-to-market for Physical AI by sourcing executive-level pipeline, accelerating top accounts, building EMEA-specific playbooks, enabling regional sales, and converting lighthouse wins into sustained cloud consumption across robotics, autonomy, simulation, and related AI-native industries.

Design rigorous, deterministic advanced physics problems and provide complete verified solutions for AI training and evaluation. Create reproducible simulations or computational workflows (using Python and scientific libraries), document reasoning clearly, and ensure technical precision. Contribute to problem design that tests deep multi-step physical reasoning.

Lead and build Axelera's AI Infrastructure Systems division to deliver datacenter-class hardware from accelerator cards and OAM/UBB modules to 1U/2U racks. Own architecture, schematics, PCB/layout review, power/thermal/mechanical design, BMC/firmware, bring-up, validation, qualification, NPI, and ramp with CMs/ODMs. Align roadmaps with silicon, SDK, and product teams, engage customers and partners, set engineering processes, manage budget and vendor relationships, and mitigate technical risks through hands-on leadership.

Lead design, training, and evaluation of LLMs for translation and language-quality tasks; build robust evaluation frameworks; architect agentic multi-model workflows; own model development from data curation to production; run reproducible experiments; collaborate with product and engineering and mentor researchers.

Lead design and delivery of AI-powered features for CLion and C++ workflows. Architect AI integrations and agent tools, prototype and validate debugging, code-understanding, refactoring, and navigation workflows, build benchmarks and evaluation frameworks, and collaborate with product, ML, QA, and engineering teams to set technical direction and roadmap for AI-assisted C++ development.

Design and implement agentic tools, translating product needs to production, scale prototypes, improve semantic search, build evaluation pipelines.

The AI-First Full-Stack Engineer will lead full-stack development using Node.js and Next.js, integrating AI workflows and orchestrating Claude agent teams for efficient engineering processes, ensuring compliance with healthcare standards.

Own end-to-end product for a slice of Nebius AI compute platform: define strategy, APIs, and roadmaps; drive cross-team delivery; conduct structured discovery; measure adoption and platform outcomes; engage engineering as a technical peer; and close operational feedback loops to improve reliability and customer experience.

Lead development of an autonomous agentic AI scientist for drug discovery: architect multi-step reasoning agents, bridge AI and wet-lab experiment design, prototype to productionize agentic systems, publish research, and collaborate with biological experts.

The Senior Product Manager will own the strategic roadmap, lead market research, manage monetization strategies, and mentor product managers within an AI and EdTech environment.

Lead and grow a distributed AI engineering team to build and operate scalable production AI platforms, model-serving, inference and training environments, CI/CD, observability, and integrations. Drive architecture, delivery, vendor evaluation, and operational readiness while partnering with global stakeholders to adopt AI across media and localization workflows.

Lead and scale full-funnel B2B demand generation using paid acquisition, ABM, field marketing, and AI-driven automation. Build and optimize landing pages, email sequences, funnels, and campaign performance to drive MQLs and pipeline. Collaborate with Sales, Content, and Design, run experiments, and measure growth metrics (CPL, CAC, conversion rates) while leveraging LLM agents and marketing automation to accelerate execution.

Author and refine a systems-engineering curriculum for experienced engineers: shape syllabus, define learning objectives, produce and fact-check lessons using AI tools, design hands-on projects and rubrics, and iterate with LX designers to meet milestone deliverables over a 4–6 month, ~15–20 hr/week engagement.

Build and ship LLM- and agent-powered product experiences for North, designing interfaces, evals, observability, and feedback loops to improve reliability and user outcomes. Collaborate with modelling, product, design, and customers to turn failures and feedback into measurable product and model improvements.

Lead applied research and system design for agent-native search: build multi-stage retrieval, ranking, and grounding methods for LLM-driven, iterative agent workflows; deploy high-throughput, low-latency production systems; define evaluation metrics; run experiments and mentor engineers.

Lead design and deployment of expert and generalist robot policies using hierarchical planning, reinforcement learning, and hybrid methods. Build real and simulated datasets, guide sensor selection and integration, collaborate with embedded and hardware teams, and contribute to AI platform architecture, CI/CD, and MLOps. Mentor engineers and drive technical roadmap for production-ready robotics solutions.

Join a client-facing squad as a hands-on Senior Full-Stack Engineer working across Kotlin backends and React/TypeScript frontends. Apply AI-native delivery practices and agent/harness engineering to accelerate delivery, unblock the team, and share patterns across the organisation while using AWS and cloud data tooling.

The Principal AI Scientist will architect and implement advanced Generative AI models, train and optimize LLM systems, and collaborate across teams to enhance performance in AI applications.

Research and engineer large multimodal and reinforcement-learning models for robotic agents: design, train, evaluate models; prototype in simulation and on hardware; build data pipelines, simulation environments, and distributed training infrastructure; collaborate to scale promising approaches into production and publish results.

Design and build research prototypes and production-capable systems to enable portable, interoperable agent and model workflows. Develop model routing, provider abstractions, memory and context representations, benchmarking suites, and evaluation protocols. Run ML experiments, implement robust APIs and integration layers, collaborate across research and engineering, and communicate results via reports, demos, publications, and open-source releases.

Onboard and support client projects onto Nebius' Azure AI platform using runbooks and golden paths. Adapt Terraform modules and CI/CD pipelines, support ML workload deployment and lifecycle management, capture delivery gaps, and provide structured feedback to Platform Engineering while maintaining security and governance.

The role involves selling IFS Loops, an AI-driven solution, targeting industrial markets, with a focus on consultative sales and driving revenue growth.

The Senior Developer Relations Manager will drive AI technology adoption by engaging with ISVs and enterprise leaders, provide technical leadership in AI and computer vision, and lead thought leadership discussions for NVIDIA's AI ecosystems.