Top Artificial Intelligence Jobs in Cologne

Lead technical strategy and build scalable AI/ML platform infrastructure on AWS and Kubernetes. Design IaC, CI/CD, observability, security, and cost/capacity practices. Mentor engineers, improve deployment reliability, and enable generative AI workloads, model routing, and operational metrics across multiple environments and regions.

As a Senior Sales Engineer, you will advise healthcare organizations on interoperability, analytics, and AI solutions, supporting technical sales throughout the cycle.

Drive product marketing for Renesas automotive microcontrollers: gather global customer requirements, coordinate projects with OEMs/Tier1s, define roadmaps, support sales and support teams, manage product introductions and marketing materials, report KPIs, and coordinate with Japan.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across 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.

The role involves designing and deploying AI systems for clinical operations, developing models for decision-making, and ensuring AI implementation aligns with data governance standards. Responsibilities include collaborating across teams, enhancing operational efficiency, and advancing AI applications in a regulated environment.

The role involves consulting with clients on technical needs, delivering customized demonstrations, and contributing to sales strategies while ensuring alignment with FICO's analytics solutions.

Own partnership sourcing, negotiation, and deal execution to drive adoption of Walrus across AI and Web3 ecosystems. Build relationships with AI builders, data vendors, compute networks, and web3 partners; lead contract negotiations; and manage cross-functional integration from signing through execution.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

Assess and evaluate AI-generated technical content, craft and answer advanced ML/AI questions, identify errors and hallucinations, rank responses by correctness and clarity, and provide precise feedback to improve model performance.

The VP of Business Development will drive commercial growth in Europe, focusing on strategic opportunities with renewable energy stakeholders and building relationships to enhance market presence.

As an AI Architect, you will design and govern enterprise AI architecture, ensuring secure, scalable solutions and compliance across the organization. Responsibilities include establishing technical standards, enabling robust AI deployments, and collaborating with teams to integrate AI with the enterprise data fabric.

The Major Account Manager will consultatively sell solutions to Fortune 500 accounts, develop relationships, and create strategic account plans to drive business.

Citrine Informatics invites applicants to submit resumes for general opportunities. They review applications periodically for potential new roles in AI-driven materials and chemicals.

The role involves driving new AI software sales, engaging with executives, and leveraging industry expertise to close large enterprise deals.

Lead development of AI/ML systems for real-time applications across various industries. Responsibilities include data analysis, system architecture, developing models, mentoring, and collaborating with engineers.

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.

Implement, integrate, and support Business AI SaaS solutions for mid-sized companies; develop intelligent agents, analyze processes, contribute to system architecture and integration, gather requirements, prototype use cases, and collaborate across interdisciplinary teams to ship production features.

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.

Lead design and delivery of production-grade ML and generative AI systems for customer-facing and operational healthcare use cases. Build end-to-end pipelines, deploy and monitor models, drive AI roadmap, collaborate with product and engineering, and ensure governance, observability and compliance in a regulated environment.

Design, develop, and maintain HR automations and RPA workflows across Workday, ServiceNow, and Microsoft tools. Manage automation projects end-to-end, optimize integrations, ensure security and compliance, document solutions, and collaborate with stakeholders and developers to standardize and scale HR automation.

Design, build, and maintain production-grade GenAI systems and Python-based APIs. Implement end-to-end RAG, vector DBs, multi-agent systems, and secure MCP infrastructure. Optimize LLM integrations (OpenAI, Anthropic), event-driven architectures, and real-time messaging. Collaborate cross-functionally, create and refine prompts, and ensure reliability, scalability, and security in production generative AI solutions.

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.

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 the Sales Models portfolio (NBA, Churn, CLV), set roadmap and technical standards, manage a cross-functional Data Science and Engineering team, integrate models into Dynamics 365 and Power BI, translate model outputs into C-level decisions, and build governance and feedback loops from field sales to model iteration.